tag:blogger.com,1999:blog-326838822024-03-12T17:41:18.068-05:00BioMed NotesLife Science News and DiscussionUnknownnoreply@blogger.comBlogger135125tag:blogger.com,1999:blog-32683882.post-36801365020992061842023-03-27T10:11:00.000-05:002023-03-27T10:11:32.979-05:00Fumarate, mitochondria, and inflammation <p><span style="font-family: arial; font-size: small;">Fumarate hydratase (FH), also known as <a href=" https://en.wikipedia.org/wiki/Fumarase" target="_blank">fumarase</a>, catalyses hydration of fumarate to malate and is found in mitochondria, where it performs in the Krebs cycle, and the cytosol, where it performs in the urea cycle and in catabolizing amino acids. It is encoded by <a href="https://www.ncbi.nlm.nih.gov/homologene?cmd=Retrieve&dopt=HomoloGene&list_uids=115 " target="_blank">homologous genes</a> in bacteria, yeast, and eukaryotes. Fumarase deficiency in humans is involved in a range of symptoms from neurological abnormalities in newborns to tumors in adults.</span></p><p style="text-align: left;"><span style="font-family: arial; font-size: small;">These authors examined what happens immediately after loss of FH. They generated a mouse line with <a href="https://en.wikipedia.org/wiki/Floxing" target="_blank">floxed</a> Fh1 gene (homolog of the human FH) and crossed it with a line with ubiquitous, inducible, Cre recombinase (Rosa26). Induction of Cre caused the genetic loss of FH expression within 5 days and metabolic changes within 10 days (Fig 1). They found mitochondria swell and lose their genome (mtDNA) into the cytosol, where it triggers innate immunity (STING) and stimulates inflammation (RIG-I) including expression of interferon stimulated genes (ISGs). </span></p><p style="text-align: left;"><span style="font-family: arial; font-size: small;"></span></p><div style="text-align: left;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEi7YKRwV_pbknHB0rJjZP5RgTQyfANxELY5otGbj_rfWv959gJdL4wzp7Mhsar7neKXNy2cqCSeT0kWAL_wK5f1orhCxw20CPh7vgJdzmRFaVdtVjmmzN2O8dzCCtRnopXTgDL5VWUZfwKc59-iR4HGIHjUC2pa8bpPrdAg3jeF91U2sd6bTOA/s1290/F3a%20MMF.jpg" imageanchor="1" style="clear: left; float: left; margin-bottom: 1em; margin-right: 1em;"><img border="0" data-original-height="1290" data-original-width="704" height="400" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEi7YKRwV_pbknHB0rJjZP5RgTQyfANxELY5otGbj_rfWv959gJdL4wzp7Mhsar7neKXNy2cqCSeT0kWAL_wK5f1orhCxw20CPh7vgJdzmRFaVdtVjmmzN2O8dzCCtRnopXTgDL5VWUZfwKc59-iR4HGIHjUC2pa8bpPrdAg3jeF91U2sd6bTOA/w219-h400/F3a%20MMF.jpg" width="219" /></a><span style="font-family: arial; font-size: small;"><span style="font-family: arial; font-size: small;">Treating cultured cells with a cell-permeable derivative of fumarate, monomethylfumarate (MMF), caused similar releases of mtDNA into the cytosol and expression of ISGs (Fig 3 Shown), strongly suggesting that the accumulation of fumarate causes the changes observed after loss of FH. They also show that mtDNA is released through ‘mitochondria-derived vesicles’ (MDVs), normally used to transport ‘content without affecting the integrity of the membranes’ (Fig 4), so the process occurs under some control. Finally, they show activation of DNA-sensor and innate immunity pathways in FH-deficient renal cancers, suggesting relevance for humans.</span></span></div><span style="font-family: arial; font-size: small;"><br /></span><span style="font-family: arial; font-size: small;">Fig 3a, Fumarate causes mitochondrial changes. Overlay
panels. Cells were treated for 8 days with solvent alone (vehicle) or
with fumarate (200 or 400 uM MMF doses) then stained for DNA (green) and
mitochondria (outer membrane protein TOM20, purple). Scale bars 10 um.
Boxed area in left column expanded in right column.</span><p></p><p style="text-align: left;"><span style="font-family: arial; font-size: small;">One wonders what happens after the loss of other ancient and obscurely important cellular infrastructure.</span></p><p style="text-align: left;"><span style="font-family: arial; font-size: small;"> </span></p><p style="text-align: left;"><span style="font-family: arial; font-size: small;"></span></p><div class="separator" style="clear: both; text-align: center;"><span style="font-family: arial; font-size: small;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEizU-H4YXVAHCvxsM3CydOKpCTpjM668aDNNgV3EvKDyq1byqn_SivR2fgTpphXxORf_bWc4bKbzgNXqAsJbYKFteAe23B0IWUvy1hU7f4tkMKd699_CUnOzZIa4ZQDz4vkPDKJnOxBhfdrxg-1uRPCDQGvoHJSJqz30baw_TfFUu-zy12qB3o/s175/PMCicon.gif" imageanchor="1" style="clear: left; float: left; margin-bottom: 1em; margin-right: 1em;"><img border="0" data-original-height="35" data-original-width="175" height="35" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEizU-H4YXVAHCvxsM3CydOKpCTpjM668aDNNgV3EvKDyq1byqn_SivR2fgTpphXxORf_bWc4bKbzgNXqAsJbYKFteAe23B0IWUvy1hU7f4tkMKd699_CUnOzZIa4ZQDz4vkPDKJnOxBhfdrxg-1uRPCDQGvoHJSJqz30baw_TfFUu-zy12qB3o/s1600/PMCicon.gif" width="175" /></a></span></div><span style="font-family: arial; font-size: small;">Zecchini V, Paupe V, Herranz-Montoya I, Janssen J, Wortel IMN, Morris JL, Ferguson A, Chowdury SR, Segarra-Mondejar M, Costa ASH, Pereira GC, Tronci L, Young T, Nikitopoulou E, Yang M, Bihary D, Caicci F, Nagashima S, Speed A, Bokea K, Baig Z, Samarajiwa S, Tran M, Mitchell T, Johnson M, Prudent J, Frezza C. <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10017517/" target="_blank">Fumarate induces vesicular release of mtDNA to drive innate immunity</a>. Nature. 2023 Mar;615(7952):499-506. doi: 10.1038/s41586-023-05770-w. Epub 2023 Mar 8. PMID: 36890229; PMCID: PMC10017517. </span><p></p><p style="text-align: left;"><span style="font-family: arial; font-size: small;"><br /></span></p>Unknownnoreply@blogger.com0tag:blogger.com,1999:blog-32683882.post-80592354606608310862023-02-27T12:48:00.000-05:002023-02-27T12:48:03.287-05:00Suppressing suppressors to improve lupus? <p>Lupus patients have more inflammation and more interferon type I (alphas, beta). SLE monocytes have less NLRP12, which is part of certain <a href="https://en.wikipedia.org/wiki/Inflammasome" target="_blank">inflammasome</a>.and contributes to the activation of pro-inflammatory <a href="https://en.wikipedia.org/wiki/Caspase" target="_blank">caspases</a>. <a href=" https://en.wikipedia.org/wiki/Toll-like_receptor_7" target="_blank">TLR7</a> is important in lupus. The authors note that <a href="https://en.wikipedia.org/wiki/NLRP12" target="_blank">NLRP12</a> was ‘recently identified’ (citing a 2012 paper) as a negative regulator of TLR and NFkB activation. </p><p>They found (Fig 1) NLRP12 expression is lower in lupus patients than in healthy controls and it is inversely correlated with type I interferon (IFN-a2) expression; (Fig 2) <a href="https://en.wikipedia.org/wiki/RUNX1" target="_blank">RUNX1</a> binding sequences in the NRLP12 promoter reduced expression of a reporter gene and CRISPR knockout of RUNX1 increased NLRP12 expression induced by IFN or virus; (Fig 3) there is more RUNX1 and less NLRP12 in monocytes from lupus patients (panels I, shown) and more RUNX1 binding to NLRP12 promoters in PBMC of lupus patients (panel J). (Fig 4) IFN-induced suppression of NLRP12 is mediated by histone acetylation; (Fig 5) RUNX1 reduces NLRP12, which increases IFN, which is (also) observed in SLE; (Fig 6) NLRP12-KO mice are more pro-inflammatory and (Fig 7 & 8) develop worse disease in mouse models of lupus (pristane injection or Fas-lpr). </p><table cellpadding="0" cellspacing="0" class="tr-caption-container" style="margin-left: auto; margin-right: auto; text-align: center;"><tbody><tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEh4XJXp_KDXvI9HTa65lLDxzy2kN05kMzfdCRBAKOxPzRfRyg6Qc83s4t6DUIX9uy90dv7YNGcCGHDwcoga6ZUgdkOqWC_9YoyeaDZRCdfY2sMk9kXP0JEMOiHW3PO-9KTFnjTm0kwvIJpd1_HknymSUjfKvKPFXdnTtowgTwb7Ku2JhLvlAjw/s3218/F3-IJ.jpg" imageanchor="1" style="clear: left; margin-bottom: 1em; margin-left: auto; margin-right: auto;"><img border="0" data-original-height="1222" data-original-width="3218" height="244" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEh4XJXp_KDXvI9HTa65lLDxzy2kN05kMzfdCRBAKOxPzRfRyg6Qc83s4t6DUIX9uy90dv7YNGcCGHDwcoga6ZUgdkOqWC_9YoyeaDZRCdfY2sMk9kXP0JEMOiHW3PO-9KTFnjTm0kwvIJpd1_HknymSUjfKvKPFXdnTtowgTwb7Ku2JhLvlAjw/w640-h244/F3-IJ.jpg" width="640" /></a></td></tr><tr><td class="tr-caption" style="text-align: center;">Figure
3, panels I&J. Panel I immunoblot of proteins in lysates of CD14+
monocytes, quantified on right. Panel J ChIP (chromosome
immunoprecipitation) of PBMC. </td></tr></tbody></table><p>They do a very good job connecting pointillist dots. <br /></p><div class="separator" style="clear: both; text-align: left;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEh4hKvRUo0sEG7jOJJbkz8kbMvyqkqEvc6uHtwX11ksmIUgYLaIrGxB_wYNCENbeAJnJLObbh-iVG9KC5781gW2XM-RRB_R7e52mXR-jfAp4htvH4tAqAPobkhps7uk4j85lG1Alvybv5ZGEY_ABfxTINx86wA-BIb9BMaU1sHHNyuWjITvufM/s404/JCI.jpg" imageanchor="1" style="clear: left; float: left; margin-bottom: 1em; margin-left: 1em;"><img border="0" data-original-height="356" data-original-width="404" height="76" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEh4hKvRUo0sEG7jOJJbkz8kbMvyqkqEvc6uHtwX11ksmIUgYLaIrGxB_wYNCENbeAJnJLObbh-iVG9KC5781gW2XM-RRB_R7e52mXR-jfAp4htvH4tAqAPobkhps7uk4j85lG1Alvybv5ZGEY_ABfxTINx86wA-BIb9BMaU1sHHNyuWjITvufM/w86-h76/JCI.jpg" width="86" /></a>Tsao YP, Tseng FY, Chao CW, Chen
MH, Yeh YC, Abdulkareem BO, Chen SY, Chuang WT, Chang PC, Chen IC, Wang
PH, Wu CS, Tsai CY, Chen ST. <a href="https://pubmed.ncbi.nlm.nih.gov/36719379/" target="_blank">NLRP12 is an innate immune checkpoint for repressing IFN signatures and attenuating lupus nephritis progression</a>. J Clin Invest. 2023 Feb 1;133(3):e157272. doi: 10.1172/JCI157272. PMID: 36719379. <br /></div>Unknownnoreply@blogger.com0tag:blogger.com,1999:blog-32683882.post-71617973525541647312023-01-30T10:52:00.001-05:002023-01-31T07:57:11.424-05:00 Can’t just “get over it”: Long COVID<p>Many people have experienced lingering problems after recovery from <a href="https://en.wikipedia.org/wiki/COVID-19" target="_blank">COVID</a> infection, a condition known as <a href="https://www.cdc.gov/coronavirus/2019-ncov/long-term-effects/index.html" target="_blank">long COVID</a> or post-COVID. A Norwegian study found that <a href="https://pubmed.ncbi.nlm.nih.gov/34163090/" target="_blank">symptoms persisted for 6 months in most patients</a> (189 of 312), including most young adults. (‘Long COVID’ preferred because ‘post-COVID’ is ambiguous.) </p><p>What is long COVID? There are many symptoms, led by fatigue, loss of smell/taste, breathlessness, and cognitive impairment, with no obvious common cause or relationship. Increased blood clotting (prothrombotic) has been suspected, suggested by the involvement of the receptor for the COVID-19 spike protein, <a href="https://en.wikipedia.org/wiki/Angiotensin-converting_enzyme_2" target="_blank">ACE2</a>, but strong evidence and mechanisms have been lacking. </p><p>These authors tested the blood of 21 patients with post-COVID syndrome (PCS), averaging nearly 2 years after onset of infection. They modeled real blood flow through vessels by collecting blood samples (treated with the anti-coagulant <a href=" https://en.wikipedia.org/wiki/Anticoagulant#Laboratory_use" target="_blank">citrate</a>) and sending it through narrow tubes coated with particular proteins. They looked at the binding of <a href=" https://en.wikipedia.org/wiki/Platelet" target="_blank">platelets</a>, which are abundant cellular products that initiate blood clots upon being triggered by binding collagen. They found striking <b>increases in platelets binding to collagen</b> (shown, Figure 1a top panel). Antibodies against von Willebrand factor (VWF) produced equivalent binding though apparently with different patterns (middle panels). </p><p><table cellpadding="0" cellspacing="0" class="tr-caption-container" style="float: left;"><tbody><tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEi4RTJVVIXCNrSoCoZ6JO_4H6N2sYD5RaF3O0LLdkSYYf7x4anGG0-jIFVMJ3WXEOTpKT-8DzyLLdFp_1RYP5C_QjuTOuYoP9VdEeN2tyO5dJdGEwHwx-_NcCMQ9MwlFRKBmWf0854u3WBL7zQwp-n4UfxTpU47tLxOjJaIWLPm8P7gPDfxVtM/s1360/F1a%20platelets.jpg" imageanchor="1" style="clear: left; margin-bottom: 1em; margin-left: auto; margin-right: auto;"><img border="0" data-original-height="1290" data-original-width="1360" height="608" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEi4RTJVVIXCNrSoCoZ6JO_4H6N2sYD5RaF3O0LLdkSYYf7x4anGG0-jIFVMJ3WXEOTpKT-8DzyLLdFp_1RYP5C_QjuTOuYoP9VdEeN2tyO5dJdGEwHwx-_NcCMQ9MwlFRKBmWf0854u3WBL7zQwp-n4UfxTpU47tLxOjJaIWLPm8P7gPDfxVtM/w640-h608/F1a%20platelets.jpg" width="640" /></a></td></tr><tr><td class="tr-caption" style="text-align: center;">Figure 1A: Binding of platelets (yellow) from healthy
control blood (left) or PCS blood (right) to collagen (top), anti-VWF (middle),
or VWF (bottom). <br /></td></tr></tbody></table> </p><p>Although these intriguing findings await confirmation (by others) and follow-up, of course, they are of the utmost importance given the enormous impact of COVID. </p><p></p><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjME4aPlSmFH_AL2YKsR1s61ktaBCQdeTG5DNkorDlm3dzQzzJx4mm59CdppLaCV7PkTDzBvoqHLwmtyM1E1T9huS5UORWRLJBTDPcLK7MIUwdNJhd7D2m0nOstl1C0-glJ42byurFd4NwUdmjhb3ZHWxmRN5P2gZD7mCDoqFGGGmeL0D854bw/s400/PBMCicon.jpg" imageanchor="1" style="clear: left; float: left; margin-bottom: 1em; margin-right: 1em;"><img border="0" data-original-height="106" data-original-width="400" height="53" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjME4aPlSmFH_AL2YKsR1s61ktaBCQdeTG5DNkorDlm3dzQzzJx4mm59CdppLaCV7PkTDzBvoqHLwmtyM1E1T9huS5UORWRLJBTDPcLK7MIUwdNJhd7D2m0nOstl1C0-glJ42byurFd4NwUdmjhb3ZHWxmRN5P2gZD7mCDoqFGGGmeL0D854bw/w200-h53/PBMCicon.jpg" width="200" /></a></div>Constantinescu-Bercu A, Kessler A, de Groot R, Dragunaite B, Heightman M, Hillman T, Price LC, Brennan E, Sivera R, Vanhoorelbeke K, Singh D, Scully M. <b>Analysis of thrombogenicity under flow reveals new insights into the prothrombotic state of patients with post-COVID syndrome</b>. J Thromb Haemost. 2023 Jan;21(1):94-100. doi: 10.1016/j.jtha.2022.10.013. Epub 2022 Dec 22. PMID: <a href=" https://pubmed.ncbi.nlm.nih.gov/36695401/" target="_blank">36695401</a>; PMCID: <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9773628/pdf/main.pdf" target="_blank">PMC9773628</a>. <p></p><p><br /></p><br /><p><br /></p>Unknownnoreply@blogger.com0tag:blogger.com,1999:blog-32683882.post-83950505190104643282022-12-26T12:13:00.003-05:002022-12-26T12:15:11.287-05:00Identifying Mitochondrial Functions by ‘Multiomic’ Profiling <span style="font-family: inherit;"><span style="font-size: small;"><a href="https://en.wikipedia.org/wiki/Mitochondrion#Mitochondrial_genetics" target="_blank">Mitochondria</a> make ATP through oxidative phosphorylation, thus providing energy for nearly all cellular functions. Many human disorders are attributed to mitochondrial dysfunction. Their functions seem narrow and their genomes, known for decades, were reduced to encoding a mere 13 proteins after transferring most to the nuclear genome. However, these authors note that ‘hundreds of mitochondrial proteins lack clear functions’. They <a href="https://pubmed.ncbi.nlm.nih.gov/27669165/" target="_blank">previously</a> (Stefely 2016) applied mass spectroscopy (MS) ‘multiomics’ to assign functions to mitochondrial uncharacterized (x) proteins (MXPs) in yeast. Here, they generated using CRISPR over 200 knockout (KO) cell lines, targeting 50 nuclear genes encoded MXPs plus 66 with known functions, and assessed in each line over 8,000 proteins, over 3,000 lipids and over 200 metabolites by MS (epic undertaking!). They found high reproducibility and dynamic range, with ‘many molecules showing regulation over 3-4 orders of magnitude’. <br /></span></span><table align="center" cellpadding="0" cellspacing="0" class="tr-caption-container" style="float: left; margin-right: 1em; text-align: left;"><tbody><tr><td style="text-align: center;"><span style="font-family: inherit;"><span style="font-size: small;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEghAjRmoBkNWEYWb6n_OkEcJg5IWtinXulH3GnQ8AhPvwseXG5F2UO_zqbVQZ9Jb9Bl6yegMvcIAMp0ORI_2oG4ujoK6PfvN0ySMrgIyyDpGuiiV5NXsoTBFgWOGl_AQ8j296l8agknhrQ4_uqWR3nuTfPIx0knN9SMLl7q7icHT6J9N4eA87Y/s1410/F2e%20SLC30A9-KO.jpg" style="margin-left: auto; margin-right: auto;"><img border="0" data-original-height="992" data-original-width="1410" height="450" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEghAjRmoBkNWEYWb6n_OkEcJg5IWtinXulH3GnQ8AhPvwseXG5F2UO_zqbVQZ9Jb9Bl6yegMvcIAMp0ORI_2oG4ujoK6PfvN0ySMrgIyyDpGuiiV5NXsoTBFgWOGl_AQ8j296l8agknhrQ4_uqWR3nuTfPIx0knN9SMLl7q7icHT6J9N4eA87Y/w640-h450/F2e%20SLC30A9-KO.jpg" width="640" /></a></span></span></td></tr><tr align="left"><td class="tr-caption"><span style="font-family: inherit;"><span style="font-size: small;">Fig 2e. Relative protein abundance in SLC30A9 KO cells compared to WT
(“wild type”, i.e., normal) cells versus statistical significance with
noted mitochondrial ribosome (black), OxPhos (blue), and mtDNA-encoded
(red) proteins.</span></span></td></tr></tbody></table><p><span style="font-family: inherit;"><span style="font-size: small;">Some assessments confirmed expectations or were mild surprises, e.g.,
the importance of ALDH18A1 or NADK1 in proline synthesis (Fig 2a).
Others revealed ‘new biology’, such as a key role for the putative zinc
transporter SLC30A9 in mitochondrial ribosome and OxPhos proteins (Fig
2e, shown). They also found that one ’upstream (open) reading frame’
(<a href="https://www.genecards.org/cgi-bin/carddisp.pl?gene=PYURF" target="_blank">PYURF</a>) is a chaperone essential for complex I and coQ
synthesis, linked a transporter (SLC30A9) to ribosomes, and found a
second gene (<a href="https://www.genecards.org/cgi-bin/carddisp.pl?gene=RAB5IF&keywords=RAB5IF" target="_blank">RAB5IF</a>) contributing to developmental
disorders. They offer their “8.3 million distinct
biomolecule measurements” <a href="https://www.mitomics.app/" target="_blank">online</a> to help others ascribe additional
functions, a promising resource. </span></span><span style="font-family: inherit;"><span style="font-size: small;"><br /><br /></span></span></p><div class="separator" style="clear: both; text-align: center;"><span style="font-size: small;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhlKKxA0qtFdD6IzWuGnb9h_r1bMJcRSQXUHFxDHYqobszXbV39yDQAQwfEA4bkNbd6GQNn8RZ5HZJIJJzciuuZxoMxZPqh2jrzv3DoY-wx4irAN2o53CnKJIOLZfk3_ALeOSfTZkUwfyPkWukj-ouV5wo6mlA-vOceOKv6J3Myh01bnvB279E/s175/PMCicon.gif" style="clear: left; float: left; margin-bottom: 1em; margin-right: 1em;"><img border="0" data-original-height="35" data-original-width="175" height="35" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhlKKxA0qtFdD6IzWuGnb9h_r1bMJcRSQXUHFxDHYqobszXbV39yDQAQwfEA4bkNbd6GQNn8RZ5HZJIJJzciuuZxoMxZPqh2jrzv3DoY-wx4irAN2o53CnKJIOLZfk3_ALeOSfTZkUwfyPkWukj-ouV5wo6mlA-vOceOKv6J3Myh01bnvB279E/s1600/PMCicon.gif" width="175" /></a></span></div><span style="font-size: small;">Rensvold JW,
Shishkova E, Sverchkov Y, Miller IJ, Cetinkaya A, Pyle A, Manicki M,
Brademan DR, Alanay Y, Raiman J, Jochem A, Hutchins PD, Peters SR, Linke
V, Overmyer KA, Salome AZ, Hebert AS, Vincent CE, Kwiecien NW, Rush
MJP, Westphall MS, Craven M, Akarsu NA, Taylor RW, Coon JJ, Pagliarini
DJ. Defining mitochondrial protein functions through deep multiomic
profiling. Nature. 2022 Jun;606(7913):382-388. doi:
10.1038/s41586-022-04765-3. Epub 2022 May 25. PMID: 35614220; PMCID:
<a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9310563/" target="_blank">PMC9310563</a>. <br />NB <a href="https://pubpeer.com/publications/8D215296524EBF6FCF468CA9AABFE4" target="_blank">PubPeer</a> comment raises concerns regarding the methods, interpretations, and conclusions. </span><p></p>Unknownnoreply@blogger.com0tag:blogger.com,1999:blog-32683882.post-68743040034262563982022-12-16T11:09:00.002-05:002022-12-16T12:04:52.504-05:00Seasonal flu vaccination: short term protection, long term risk? Influenza (flu) <a href="https://pubmed.ncbi.nlm.nih.gov/29446233/" target="_blank">sickens millions</a> and kills many thousands of Americans each year. Vaccination is intended to reduce the number cases and severity of illness. The flu virus changes its coat proteins each year, a ‘shape-shifting’ behavior that challenges the timely production of vaccines that are effective against flu variants. The US CDC evaluates vaccine effectiveness (VE) in thousands of outpatient respiratory illness patients, usually finding <a href="https://www.cdc.gov/mmwr/volumes/71/wr/pdfs/mm7110a1-H.pdf" target="_blank">substantial vaccine protection</a> with <a href=" https://www.hrsa.gov/vaccine-compensation" target="_blank">little risk</a> Consequently, its Advisory Committee on Immunization Practices (ACIP) as well as the World Health Organization (WHO) <a href=" https://www.cdc.gov/flu/prevent/vaccinations.htm" target="_blank">recommend</a> annual immunization of everyone over 6 months old unless contraindicated. <br /> <br />Here, the authors surveyed vaccination over 10 years among several thousand Japanese school children and several hundred school staff adults. Of the many <a href="https://www.cdc.gov/flu/prevent/different-flu-vaccines.htm" target="_blank">forms of flu vaccine</a>, Japan uses a quadrivalent (4 strains; trivalent prior to 2014) “split” vaccine based on influenza <a href="https://en.wikipedia.org/wiki/Hemagglutinin_(influenza)" target="_blank">hemagglutinin</a> (HA). “Split” vaccine means the virus was ‘disrupted’ by detergent (the equivalent of ‘heat killed’; viruses aren’t alive). The flu viruses used to prepare the vaccine are grown in eggs; alternative quadrivalent preparations are available for those with allergies to eggs, including <a href="https://www.cdc.gov/flu/prevent/qa_flublok-vaccine.htm" target="_blank">Flublok</a> and <a href="https://www.cdc.gov/flu/prevent/cell-based.htm" target="_blank">Flucelvax</a>. <br /><br />They found that morbidity was reduced in vaccinated elementary school students but elevated in middle school students (Fig 1). Most people who had been vaccinated ‘from infancy’ were also vaccinated in the 2019-2020 season (Fig. 2). Moreover, they “found that <b>morbidity was significantly higher among elementary (P < 0.001) and middle (P < 0.05) school students who had been vaccinated since infancy than among those who had not been vaccinated since infancy</b>” (Figure 3, shown). <br /><table align="center" cellpadding="0" cellspacing="0" class="tr-caption-container" style="margin-left: auto; margin-right: auto; text-align: center;"><tbody><tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhMm9hCgJSSfxUyhAoJz55dk-aQptPWXKrsIkpfdrFLZFfMqsHcdU_gv_VlB39b8y3Kmp4B6CJqj-lEBlkW7ZXu1X1EZrpRuw8XUdhUBGIk154AbeElqSArMl5mgBnMgMhlQjlgBBrFndALf3ngePg6yYKwctcq0eb12Jl414AdokgDta5yOuk/s1876/F3%20vaccine%20from%20infancy.jpg" style="margin-left: auto; margin-right: auto;"><img border="0" data-original-height="1032" data-original-width="1876" height="352" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhMm9hCgJSSfxUyhAoJz55dk-aQptPWXKrsIkpfdrFLZFfMqsHcdU_gv_VlB39b8y3Kmp4B6CJqj-lEBlkW7ZXu1X1EZrpRuw8XUdhUBGIk154AbeElqSArMl5mgBnMgMhlQjlgBBrFndALf3ngePg6yYKwctcq0eb12Jl414AdokgDta5yOuk/w640-h352/F3%20vaccine%20from%20infancy.jpg" width="640" /></a></td></tr><tr><td class="tr-caption" style="text-align: center;">Fig. 3 Relationship between morbidity and vaccination from infancy. </td></tr></tbody></table><p></p><p>These
data are self-reported via questionnaires, and therefore extra
subjective. The authors propose no mechanism for how annual vaccination
could cause increased morbidity. It seems probable that the association
is not direct, not causative, but indirect through other behavioral or
health status factors. This is an intriguing finding that should be
analyzed and study that should be repeated. <br /></p><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEieDSVpnqennRV78TSuHoE0ztZfYW0WeLKAUZDOoBq0RVQhwRNmqrCdg5REnSHFJGs0Ey1xxZzADle2-qpwL8voDM0gmyHn91RDTHErFEToL20Ic2a5in0JzvndRJvA3cydEdM_8ZxvXax4EW7T7jZuUZ9cCdbvcOj9IG7MPCDshUIJNTVcZvc/s468/PubMedGov.jpg" style="clear: left; float: left; margin-bottom: 1em; margin-right: 1em;"><img border="0" data-original-height="134" data-original-width="468" height="43" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEieDSVpnqennRV78TSuHoE0ztZfYW0WeLKAUZDOoBq0RVQhwRNmqrCdg5REnSHFJGs0Ey1xxZzADle2-qpwL8voDM0gmyHn91RDTHErFEToL20Ic2a5in0JzvndRJvA3cydEdM_8ZxvXax4EW7T7jZuUZ9cCdbvcOj9IG7MPCDshUIJNTVcZvc/w149-h43/PubMedGov.jpg" width="149" /></a></div>Kajiume
T, Mukai S, Toyota N, Kanazawa I, Kato A, Akimoto E, Shirakawa T. <a href="https://pubmed.ncbi.nlm.nih.gov/36474168/" target="_blank">Effectiveness of seasonal influenza vaccine in elementary and middle schools: a 10-year follow-up investigation</a>. BMC Infect Dis. 2022 Dec
6;22(1):909. doi: 10.1186/s12879-022-07898-y. PMID: 36474168; PMCID:
PMC9724312. <br /><p></p>Unknownnoreply@blogger.com0tag:blogger.com,1999:blog-32683882.post-20506932124523087502022-11-16T11:33:00.000-05:002022-11-16T11:33:00.011-05:00Protein folding by AI: wrinkles <p>Tech giants Alpha and Meta (Google and Facebook) applied their Artificial Intelligence (AI) to fold proteins computationally, predicting 3-dimensional shapes from the 1-dimensional sequence data. Meta’s paper is still paywalled (<a href="https://www.biorxiv.org/content/10.1101/2022.07.20.500902v2 " target="_blank">preprint</a>) but AlphaFold’s Nature papers from last year are available (<a href="https://pubmed.ncbi.nlm.nih.gov/34265844/" target="_blank">Jumper</a>, <a href="https://pubmed.ncbi.nlm.nih.gov/34293799/" target="_blank">Tunyasuvunakool</a>). </p><p>The AlphaFold authors noted that the ~100,000 protein structures determined by conventional experimental means are a small portion of the “billions” extant in nature. Previous approaches “focus on either the physical interactions or the evolutionary history”, which they say relies on the availability of close homologues or works for (only) a few, small proteins and is otherwise “computationally intractable” (too hard). They evaluated in the 87 protein domains comprising the 14th Critical Assessment of (protein) Structure Prediction (<a href="https://www.predictioncenter.org/casp14/doc/CASP14_Abstracts.pdf " target="_blank">CASP14</a>) dataset, structures not yet deposited in the public Protein Data Bank (<a href="https://www.nist.gov/publications/protein-data-bank-pdb" target="_blank">PDB</a>). This permits a ‘blind’ (apriori) comparison of AI methods, by comparing their predictions with the newly-solved structures. </p><p><table align="center" cellpadding="0" cellspacing="0" class="tr-caption-container" style="margin-left: auto; margin-right: auto;"><tbody><tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjG-xwYM-U3fcCiL0zFobEya--ysIYpwcfhGQb330DRd9kljcpOw4n-1Zij46RywhpM3HP71OdYeICeknWtPlq6Y_7XeKMBvR4teHwLvWz8sL_pUKvrTbrTYwCvyq6Rhg-Xq173U8qgQ8bPflJwgCucLJkfCWAn36L6jeBckVPZSzaOC8IqUhQ/s1856/Fig%201abc%20Jumper%20.jpg" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" data-original-height="772" data-original-width="1856" height="266" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjG-xwYM-U3fcCiL0zFobEya--ysIYpwcfhGQb330DRd9kljcpOw4n-1Zij46RywhpM3HP71OdYeICeknWtPlq6Y_7XeKMBvR4teHwLvWz8sL_pUKvrTbrTYwCvyq6Rhg-Xq173U8qgQ8bPflJwgCucLJkfCWAn36L6jeBckVPZSzaOC8IqUhQ/w640-h266/Fig%201abc%20Jumper%20.jpg" width="640" /></a></td></tr><tr><td class="tr-caption" style="text-align: center;">Fig 1. a. Scores. b. Backbone. c. Side chains<br /></td></tr></tbody></table> By this measure, AlphaFold is much better than its competitors (Fig 1a, shown, predicted vs experimental). It gains accuracy on backbone and side chains (1b, c) “by incorporating novel neural network architectures and training procedures based on the evolutionary, physical and geometric constraints of protein structures”. Using “multiple sequence alignments (MSAs) and pairwise” comparisons, it “predicts the 3D coordinates of all heavy atoms for a given protein using the primary amino acid sequence and aligned sequences of homologues as inputs”. So give it a bunch of similar sequences and structures and voila! it gives the ‘new’ one. Thy describe the process and you can download to code to inspect, modify, run yourself (<a href="https://github.com/deepmind/alphafold" target="_blank">open source</a>). </p><p>While impressive, this is a very constrained set of structures, nothing justifying the claims made in the popular press of solving all proteins. To be comprehensive, it seems that AI will have to consider biology, implement means of including the amino-terminal-first synthesis, nucleation, domain folding, insertion into a membrane, and above all interaction with chaperone proteins. </p><p></p><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhP4mtg77NVFgCCcJTdFqm-vGDPIo_GpusvGT2og4B2f_VsbC9bz9gHW9tJti9G5paoVnQXKOM67ppTFPR5MRZMHaRu_USfsird5xi3Loube4DZpMKRujSmpn7OaTuQ8CloOFOBALdB5k0_F-mng9VpxBbLuR282qKq46Y96gVlnx_2_wOy448/s468/PubMedGov.jpg" imageanchor="1" style="clear: left; float: left; margin-bottom: 1em; margin-right: 1em;"><img border="0" data-original-height="134" data-original-width="468" height="58" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhP4mtg77NVFgCCcJTdFqm-vGDPIo_GpusvGT2og4B2f_VsbC9bz9gHW9tJti9G5paoVnQXKOM67ppTFPR5MRZMHaRu_USfsird5xi3Loube4DZpMKRujSmpn7OaTuQ8CloOFOBALdB5k0_F-mng9VpxBbLuR282qKq46Y96gVlnx_2_wOy448/w200-h58/PubMedGov.jpg" width="200" /></a></div>Jumper J, Evans R, Pritzel A, Green T, Figurnov M, Ronneberger O, Tunyasuvunakool K, Bates R, Žídek A, Potapenko A, Bridgland A, Meyer C, Kohl SAA, Ballard AJ, Cowie A, Romera-Paredes B, Nikolov S, Jain R, Adler J, Back T, Petersen S, Reiman D, Clancy E, Zielinski M, Steinegger M, Pacholska M, Berghammer T, Bodenstein S, Silver D, Vinyals O, Senior AW, Kavukcuoglu K, Kohli P, Hassabis D. <a href="https://www.nature.com/articles/s41586-021-03819-2" target="_blank">Highly accurate protein structure prediction with AlphaFold</a>. Nature. 2021 Aug;596(7873):583-589. doi: 10.1038/s41586-021-03819-2. Epub 2021 Jul 15. PMID: 34265844; PMCID: PMC8371605. <br /><p></p>Unknownnoreply@blogger.com0tag:blogger.com,1999:blog-32683882.post-56972717598211593572022-11-12T13:13:00.000-05:002022-11-12T13:13:15.355-05:00Leptin boosts protective vaccine responses <p><span style="font-family: inherit;"><span style="font-size: medium;">Follicular helper T cells (<a href="https://en.wikipedia.org/wiki/Follicular_B_helper_T_cells" target="_blank">Tfh</a>) support B cell development and production of antibodies, essential for a protective vaccination response. Metabolism has been linked to T cell development and the metabolic hormone <a href="https://en.wikipedia.org/wiki/Leptin" target="_blank">leptin</a> varies up to 10-fold among healthy people. Here, the investigators asked whether leptin levels might influence T cell development and contribute to variability in vaccine responses. </span></span></p><p><span style="font-family: inherit;"><span style="font-size: medium;">Within a cohort of 76 healthy adults, they found non-responders to influenza vaccination had on average 2.5-fold lower serum leptin levels, with non-responders 10-fold more frequent in the low leptin group (fig 1ab). Tfh counts correlate with leptin levels (fig 2). Similar observations were made among older flu vaccine recipients (age >64 yr) and young Hepatitis B vaccine (HBV) recipients. Adding leptin to T cells cultured in vitro increased Tfh markers and production of IL-21 (fig 2e). </span></span></p><p><span style="font-family: inherit;"><span style="font-size: medium;">In mice, they found leptin in areas of B cell development and leptin receptors on Tfh cells. Leptin receptor deficiency reduced antibody responses (fig 3b, c) and (consequently) allowed viral growth (panel a) in mice infected with H1N1 influenza. Tfh in leptin-receptor-deficient mice produced less IL-21 (fig 5b) and supplemental IL-21 restored most antibody production (fig 5a). IL-21 production is abrogated in T cells lacking STAT3 (fig 5g), strongly supporting a mechanism involving STAT3 and IL-21. </span></span></p><p></p><table cellpadding="0" cellspacing="0" class="tr-caption-container" style="margin-left: auto; margin-right: auto; text-align: center;"><tbody><tr><td style="text-align: center;"><span style="font-family: inherit;"><span style="font-size: medium;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgZoYS6WVwDB-5wI6UBw_QPZpNhmnAeU2IAfaLBZ9Avc9VX8bkCriPfWRF3Pz_7BUXn4I7bu5YGHK1KVWaobigfHlo5exdeKOOGyoRDIjgot4yphAJ9QDwDqYEwPD-uyeBp5qqYk5IJtc3tBesJYnp7vnAptXSiuCuQdNdFsLEARlSpwZSVcGU/s1692/f7ab%20leptin%20flu.jpg" style="clear: left; margin-bottom: 1em; margin-left: auto; margin-right: auto;"><img border="0" data-original-height="596" data-original-width="1692" height="226" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgZoYS6WVwDB-5wI6UBw_QPZpNhmnAeU2IAfaLBZ9Avc9VX8bkCriPfWRF3Pz_7BUXn4I7bu5YGHK1KVWaobigfHlo5exdeKOOGyoRDIjgot4yphAJ9QDwDqYEwPD-uyeBp5qqYk5IJtc3tBesJYnp7vnAptXSiuCuQdNdFsLEARlSpwZSVcGU/w640-h226/f7ab%20leptin%20flu.jpg" width="640" /></a></span></span></td></tr><tr><td class="tr-caption" style="text-align: center;"><span style="font-family: inherit;"><span style="font-size: medium;">Fig 7. Leptin protects from fasting-induced susceptibility to influenza. </span></span></td><td class="tr-caption" style="text-align: center;"><span style="font-family: inherit;"><span style="font-size: medium;"><br /></span></span></td><td class="tr-caption" style="text-align: center;"><span style="font-family: inherit;"><span style="font-size: medium;"><br /></span></span></td></tr></tbody></table><span style="font-family: inherit;"><span style="font-size: medium;"> </span></span><p></p><p><span style="font-family: inherit;"><span style="font-size: medium;">They could transiently reduce serum leptin levels by ‘fasting’ (starving) mice on alternate days 5 to 15 days after infection with influenza (Fig 7a, shown above). This timing chosen to avoid interfering with T cell priming (d 0-5) and focus on peak Tfh development (starting d5). Supplemental leptin protected against influenza (panel b), underscoring the significance of this pathway. <br /><br /></span></span></p><div class="separator" style="clear: both; text-align: center;"><span style="font-size: medium;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhe8VK1IDcpM_wZ9ofZvORk1XIrEOJGZbo3gMcbidDACkmBkezUAynsJ81ZLznFIJB-srBADSHbwKcC6EVJsOs6Ia4e_1pqZFbJ8WZc0-Ikv7rRk6t6kmfLw8jiE-xVnWAqU1TBun76D5P2b7yKLv8YWNV6zD2ACZcw0cg9EkG-J7Tw24UdP_Y/s175/PMCicon.gif" style="clear: left; float: left; margin-bottom: 1em; margin-right: 1em;"><img border="0" data-original-height="35" data-original-width="175" height="40" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhe8VK1IDcpM_wZ9ofZvORk1XIrEOJGZbo3gMcbidDACkmBkezUAynsJ81ZLznFIJB-srBADSHbwKcC6EVJsOs6Ia4e_1pqZFbJ8WZc0-Ikv7rRk6t6kmfLw8jiE-xVnWAqU1TBun76D5P2b7yKLv8YWNV6zD2ACZcw0cg9EkG-J7Tw24UdP_Y/w200-h40/PMCicon.gif" width="200" /></a></span></div><span style="font-size: medium;">Deng J, Chen Q, Chen Z, Liang K, Gao X, Wang X, Makota FV, Ong HS, Wan Y, Luo K, Gong D, Yu X, Camuglia S, Zeng Q, Zhou T, Xue F, He J, Wei Y, Xiao F, Ma J, Hill DL, Pierson W, Nguyen THO, Zhou H, Wang Y, Shen W, Sun L, Li Z, Xia Q, Qian K, Ye L, Rockman S, Linterman MA, Kedzierska K, Shen N, Lu L, Yu D. <b>The metabolic hormone leptin promotes the function of TFH cells and supports vaccine responses</b>. Nat Commun. 2021 May 24;12(1):3073. doi: 10.1038/s41467-021-23220-x. PMID: 34031386; PMCID: <a href="https://pubmed.ncbi.nlm.nih.gov/34031386/" target="_blank">PMC8144586</a>. <br /></span><p></p>Unknownnoreply@blogger.com1tag:blogger.com,1999:blog-32683882.post-21669265567272179782022-11-02T10:44:00.003-05:002022-11-02T10:44:36.287-05:00Physical activity increases gut bacteria diversity <p>Previous work established associations in humans between physical activity and reduced obesity, reduced mortality, and improved cardiovascular health. Physical activity has been also associated with the microbiome in animals. Here, the relationship between physical activity and <a href="https://en.wikipedia.org/wiki/Human_microbiome#Gastrointestinal_tract" target="_blank">microbiome in humans</a> was investigated.</p><p>The authors studied a cohort of 720 adults, citizens of Wisconsin, average age 55 years, 83% White, 10% Black, 42% male. Gut microbial, (bacterial) composition was assessed using sequencing the V3-V4 region of <a href="https://en.wikipedia.org/wiki/16S_ribosomal_RNA" target="_blank">16S</a> rRNA extracted from stool samples. Note this is only a subset of the ‘<a href=" https://www.niehs.nih.gov/health/topics/science/microbiome/index.cfm" target="_blank">microbiome</a>’, not include non-bacterial components such as fungi, viruses, etc. </p><p>They monitored physical activity using accelerometers worn on the hip (activity) or wrist (sleep). Participants also self-reported whether in a typical week they walked or biked at least 10 minutes continuously to get around. Those who responded ‘yes’ were classified as participating in ‘active transportation’. Note this is a threshold of less than half a mile a week, walking only about 100 m per day. </p><p><table cellpadding="0" cellspacing="0" class="tr-caption-container" style="float: left;"><tbody><tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEj3S-q89oANA1EP-oC2BpD_CGFpupSrPsZ8bcJ3JI_lJAZAE7XBHT98x5eL_rPsTvyMTlBPTT6im-Cz9hRwa-G6x4ME2wJNqlmEz2eT9fz_lpjPQzbDldOYp5VosqMs5yfrMlfDEOJvAsDBChyNk6ZiR0dwjUXg_AnRHzszcyIHz4F-f0j1NSk/s2628/T2%20gut%20activity.jpg" imageanchor="1" style="clear: left; margin-bottom: 1em; margin-left: auto; margin-right: auto;"><img border="0" data-original-height="450" data-original-width="2628" height="110" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEj3S-q89oANA1EP-oC2BpD_CGFpupSrPsZ8bcJ3JI_lJAZAE7XBHT98x5eL_rPsTvyMTlBPTT6im-Cz9hRwa-G6x4ME2wJNqlmEz2eT9fz_lpjPQzbDldOYp5VosqMs5yfrMlfDEOJvAsDBChyNk6ZiR0dwjUXg_AnRHzszcyIHz4F-f0j1NSk/w640-h110/T2%20gut%20activity.jpg" width="640" /></a></td></tr><tr><td class="tr-caption" style="text-align: center;">Table 2. Linear mixed effects models (adjusted for characteristics,
Table 1). CI, confidence interval; SD, standard deviation; MVPA,
moderate to vigorous physical activity; ** p<0.05. *** p < 0.01. </td></tr></tbody></table>They identified 865 unique bacterial taxa, largely encompassed by about 20 abundant phyla (Fig 1). They observed no change in bacterial <a href="https://en.wikipedia.org/wiki/Alpha_diversity" target="_blank">diversity</a> in participants who engaged in moderate-to-vigorous activity (line 2, Table 2, shown) or active transportation (line 3). However, when they analyzed those participants who engaged in higher levels of active transportation, at least 1 standard deviation (SD) above the average, they observed significant increases in bacterial diversity (line 4). <br /><br />They also found the abundance of an unknown family from order Clostridiales was associated with increased weekly MVPA minutes. They conclude that their results “point to a potential pathway by which the gut micro- biota may be linked to physical activity and other well established health benefits”.</p><p></p><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjuskMbZDo1mxpp3fnfruui4fPD6P2XeAtbII5ehEFan4fc6hfHNdZubZ7omEJcxm5EaugGw9ODK9irMxHqcKDd2tJQWrczSEOpF74in1l2QMrX-DafFNzwAx2u852aLVpXzJaONhtiBJhKLzQsLgioIDbiYl1v6KJZrjGm04iMCSH08ecztAc/s175/PMCicon.gif" imageanchor="1" style="clear: left; float: left; margin-bottom: 1em; margin-right: 1em;"><img border="0" data-original-height="35" data-original-width="175" height="35" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjuskMbZDo1mxpp3fnfruui4fPD6P2XeAtbII5ehEFan4fc6hfHNdZubZ7omEJcxm5EaugGw9ODK9irMxHqcKDd2tJQWrczSEOpF74in1l2QMrX-DafFNzwAx2u852aLVpXzJaONhtiBJhKLzQsLgioIDbiYl1v6KJZrjGm04iMCSH08ecztAc/s1600/PMCicon.gif" width="175" /></a></div>Holzhausen EA, Malecki KC, Sethi AK, Gangnon R, Cadmus-Bertram L, Deblois CL, Suen G, Safdar N, Peppard PE. Assessing the relationship between physical activity and the gut microbiome in a large, population-based sample of Wisconsin adults. PLoS One. 2022 Oct 26;17(10):e0276684. doi: 10.1371/journal.pone.0276684. PMID: 36288361; PMCID: <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9605031/" target="_blank">PMC9605031</a>. <br /><p></p>Unknownnoreply@blogger.com0tag:blogger.com,1999:blog-32683882.post-27136446693629696222022-10-27T08:37:00.001-05:002022-10-27T08:37:32.561-05:00When viruses cohabit: Flu + RSV = Hybrid Frankenvirus <p>Experts <a href="https://www.reuters.com/business/healthcare-pharmaceuticals/covid-flu-rsv-this-us-winter-why-experts-are-worried-2022-10-26/" target="_blank">worry</a> that this winter might be made miserable by unwelcome visitors: something new, coronavirus variants, something flu (influenza A virus, IAV) and something blew, respiratory syncytial virus (RSV). What happens when somebody hosts IAV and RSV at the same time? <br /><br />These investigators infected cultured human lung cells, A549 cells, and confirmed previous reports that coinfection reduces RSV but not IAV replication (Fig 1). Despite producing lower titer, they observed that infection with IAV appeared to increase the rate of coinfection by RSV. <br /><table cellpadding="0" cellspacing="0" class="tr-caption-container" style="float: left;"><tbody><tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiF1GJMgA3zglRb5OrMeot36e0tq72inNXXCAbRuo7EloGbNVFsiJE7vXlRvgwdPhzOgBEaaIVneKv_HFZMlFVkWp0AMtJt5135aTP-zHOsA_u9wsFImqFVV-hHxavFYrXiW_GtUfFrxk1vUhyFaQrw7uOBWAU5yKUOej9WUCSYnD6AxOF5Xfw/s1424/F3b%20filament.jpg" imageanchor="1" style="clear: left; margin-bottom: 1em; margin-left: auto; margin-right: auto;"><img border="0" data-original-height="1424" data-original-width="1194" height="400" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiF1GJMgA3zglRb5OrMeot36e0tq72inNXXCAbRuo7EloGbNVFsiJE7vXlRvgwdPhzOgBEaaIVneKv_HFZMlFVkWp0AMtJt5135aTP-zHOsA_u9wsFImqFVV-hHxavFYrXiW_GtUfFrxk1vUhyFaQrw7uOBWAU5yKUOej9WUCSYnD6AxOF5Xfw/w335-h400/F3b%20filament.jpg" width="335" /></a></td></tr><tr><td class="tr-caption" style="text-align: center;">Fig 3b. Filament with features of IAV and RSV.<br /></td></tr></tbody></table></p><p>IAV and RSV are enveloped viruses that bud from the cell membrane with
characteristic glycoproteins hemagglutinin (HA) and fusion (F),
respectively. Having detected HA in areas of RSV budding from coinfected
cells, the authors hypothesized that some virions would contain
components of both viruses. Indeed, they observed many filaments,
typical of RSV, with proteins from both viruses, albeit segregated (Fig
2a-e). A remarkable scanning electron micrograph appears to show hybrid
viral particles (HVP) budding from the filaments (2f, red arrows).
They analyzed the hybrid buds using cryo-ET and were able to ‘segment’
features of both viruses (shown, Fig 3b): mostly IAV virions budding
from mostly RSV filaments. </p><p>Amazing biology, but what does it mean clinically? The authors found that the hybrid virions contained IAV capable of infecting cells that had been depleted of their sialic acids, which bind HA, by treatment with neuraminidase (NA), Fig. 4-5). This could be an important mechanism widening the range of infected cells. <br /><br />Haney J, Vijayakrishnan S, Streetley J, Dee K, Goldfarb DM, Clarke M, Mullin M, Carter SD, Bhella D, Murcia PR. <a href="https://rdcu.be/cYmYT" target="_blank">Coinfection by influenza A virus and respiratory syncytial virus produces hybrid virus particles</a>. <a href="https://www.nature.com/articles/s41564-022-01242-5" target="_blank">Nat Microbiol</a>. 2022 Oct 24. doi: 10.1038/s41564-022-01242-5. Epub ahead of print. PMID: <a href="https://pubmed.ncbi.nlm.nih.gov/36280786/" target="_blank">36280786</a>. <br /></p>Unknownnoreply@blogger.com0tag:blogger.com,1999:blog-32683882.post-56494413455628122702022-10-21T06:57:00.002-05:002022-10-21T07:03:06.611-05:00Bad news bears on life choices (vaccine hesitancy) <p><span style="font-size: small;"><span style="font-family: verdana;"><a href="https://en.wikipedia.org/wiki/Vaccine_hesitancy" target="_blank">Vaccine hesitancy</a>, a reluctance or
refusal to be vaccinated, probably began when <a href="https://en.wikipedia.org/wiki/Edward_Jenner" target="_blank">Jenner</a> invented vaccination
over two centuries ago. Vaccines have largely eliminated scourges such as
smallpox and <a href="https://en.wikipedia.org/wiki/Polio_vaccine" target="_blank">polio</a><span> </span>and greatly reduced the rates of other infectious
diseases including <a href="https://en.wikipedia.org/wiki/Influenza_vaccine" target="_blank">influenza</a>. Anti-vaccination (anti-vax)
stances stem from small, well-established risks of side-effects (managed by a <a href="https://www.hrsa.gov/vaccine-compensation" target="_blank">compensation program</a>) and big, vague worries about unrelated, even disproven associations with other maladies. COVID-19 vaccines were developed rapidly and rushed into production, potentially raising valid safely concerns.<span> </span>However, any valid concerns were allayed when the COVID-19 vaccines were tested and proven safe and effective (<a href="https://pubmed.ncbi.nlm.nih.gov/33053279/" target="_blank">Walsh 2020</a>). </span></span></p><p><span style="font-size: small;"><span style="font-family: verdana;">The cable television show Fox News Channel (FNC) amplified concerns about COVID-19 vaccines and downplayed their benefits. <span> </span>This study of viewership and vaccination covered ~2,750 counties (out of ~3,000 total) in 47 (of 50) US states documents that FNC viewers refused COVID-19 vaccination more often than the viewers of its competitors Microsoft-National Broadcasting Company (MSNBC) or Cable News Network (CNN) (Figure 2, shown). <br /></span></span></p><p class="MsoNormal"><span style="font-size: small;"><span style="font-family: verdana;"><span></span></span></span></p><table cellpadding="0" cellspacing="0" class="tr-caption-container" style="margin-left: auto; margin-right: auto; text-align: center;"><tbody><tr><td style="text-align: center;"><span style="font-size: small;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhZXznayuETRDBNfWGpf4tNEylLxkez3ceBVLFfJOo53LISEmg3Tb0uS7PfBtLXDQUs2P15Wy35sIvoZ0yT111WbWJcyz7uT_3wMd1qVry_jK4ABNAzy9gOB13dbEPl1Spyn_kGxYCIt83-IShqN2qJ7WKfiu6hwwgT4Clt4uhVvv4s94J9o4k/s1966/F2%20news%20vs%20vax.jpg" style="clear: left; margin-bottom: 1em; margin-left: auto; margin-right: auto;"><img border="0" data-original-height="962" data-original-width="1966" height="314" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhZXznayuETRDBNfWGpf4tNEylLxkez3ceBVLFfJOo53LISEmg3Tb0uS7PfBtLXDQUs2P15Wy35sIvoZ0yT111WbWJcyz7uT_3wMd1qVry_jK4ABNAzy9gOB13dbEPl1Spyn_kGxYCIt83-IShqN2qJ7WKfiu6hwwgT4Clt4uhVvv4s94J9o4k/w640-h314/F2%20news%20vs%20vax.jpg" width="640" /></a></span></td></tr><tr><td class="tr-caption" style="text-align: center;">
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<p><span style="font-family: "MinionPro"; font-size: small; font-weight: 700;">Figure 2. </span><span style="font-family: "MinionPro"; font-size: small;">Effect of network viewership on weekly vaccination rates, 2021
</span></p>
</div>
</div>
</div>
</div>
</td></tr></tbody></table><span style="font-size: small;"><span style="font-family: verdana;">A key question is whether FNC influenced its viewers to refuse vaccination (a cause) or rather were anti-vax viewers attracted to FNC’s
messaging, a consequence of playing to its audience.<span> </span>The investigators used positions in cable channel listing as ‘exogenous shifters’ of viewership (<a href="https://www.aeaweb.org/articles?id=10.1257/aer.20160812" target="_blank">Martin & Yurukoglu
2017</a>). Viewers are induced into watching more or less of a channel by variation in its position up or down the listing (Fig S3). <span> </span>They found that “exogenously higher FNC viewership due to channel position causes lower vaccine uptake”. They show that hesitancy was raised by FNC but not by competitors MSNBC or CNN (Fig 1). Moreover, resistance to vaccination against
COVID-19 but not seasonal flu… causal…. Using the channels’ position in the guides. </span></span><br /><p><span style="font-size: small;"><span style="font-family: verdana;">
</span></span></p><p class="MsoNormal"><span style="font-size: small;"><span style="font-family: verdana;">Their “results imply that watching one additional hour of [FNC]
per week for the average household reduces the number of vaccinations by
0.35–0.76 per 100 people”, which would account for a lot of ‘excess deaths’ in
many households. Not surprising when “vaccine bad” was said so much more often
on FNC than the other channels (Fig S7)! Although they found that FNC’s
influence was mostly on those under 65 years old, who are at lower risk severe
disease, those younger people are reservoirs of virus for infecting older
people. Data-driven lawyers representing survivors of FNC victims could bring
class action lawsuits.<span> </span></span></span></p><p><span style="font-size: small;"><span style="font-family: verdana;">
</span></span></p><div class="separator" style="clear: both; text-align: center;"><span style="font-size: small;"><span style="font-family: verdana;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEi02gqL6wSx0FW8b-75cBL8Psu5hBSYZimsQPC2sPiQSf7NeY50m6HCGoQykqAHWA6V6BHFgjfJ6nZkPkHw61N78EMHHCoHJeMbySysBx_1XbxQ2O8qCJBThlTv-z_w67k0GKW8kYsGpI4CqFlxqaSXdHTOdmI9XC4dMRzeSYu25kbdCyc-aWA/s322/OpenAccessIcon.jpg" style="clear: left; float: left; margin-bottom: 1em; margin-right: 1em;"><img border="0" data-original-height="322" data-original-width="200" height="43" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEi02gqL6wSx0FW8b-75cBL8Psu5hBSYZimsQPC2sPiQSf7NeY50m6HCGoQykqAHWA6V6BHFgjfJ6nZkPkHw61N78EMHHCoHJeMbySysBx_1XbxQ2O8qCJBThlTv-z_w67k0GKW8kYsGpI4CqFlxqaSXdHTOdmI9XC4dMRzeSYu25kbdCyc-aWA/w26-h43/OpenAccessIcon.jpg" width="26" /></a></span></span></div><span style="font-size: small;"><span style="font-family: verdana;">Pinna, M., Picard, L. & Goessmann, C. <a href="https://doi.org/10.1038/s41598-022-20350-0" target="_blank">Cable news andCOVID-19 vaccine uptake</a>. <i>Sci Rep</i> <b>12</b>, 16804 (2022). <br /></span></span><p><span style="font-size: small;"><style><font size="3"><span style="font-family: verdana;">@font-face
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{page:WordSection1;}</span></font></style></span></p>Unknownnoreply@blogger.com0tag:blogger.com,1999:blog-32683882.post-20633811942603417872022-10-18T11:09:00.001-05:002022-10-18T17:23:40.539-05:00Lipid metabolism and dementia<p><span style="font-family: arial;"><span style="font-size: small;">About half the human brain mass is lipid. Several brain disorders are known to be caused by abnormal lipid metabolism, disruptions in the processes of making lipids and breaking them down. Second only to Alzheimer’s in prevalence is <a href="https://en.wikipedia.org/wiki/Frontotemporal_dementia" target="_blank">frontotemporal dementia</a> (FTD), one form of which encompasses a range of social, behavioral, or language <a href="https://omim.org/entry/607485" target="_blank">disorders</a> (as opposed to memory or motor deficits seen in other disorders).
Several <a href="https://www.ncbi.nlm.nih.gov/omim/?term=frontotemporal%20dementia%20" target="_blank">genes</a> have been associated with FTD, foremost among them the conserved genes MAPT (tau), PSEN1 (presenilin), VCP (valosin containing protein) and GRN (granulin). </span></span></p><p><span style="font-family: arial;"><span style="font-size: small;"></span></span></p><div class="separator" style="clear: both; text-align: center;"><span style="font-size: small;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEj5pDDGJscW2FHci08qpcB-QeMp8hyDmkPHUwEfyZpqACNg-6h9Jvr9C6gR8mB5mNOW994DTqzbxj_9kV_Tn7co9h7VcLx4jJbLjjPWn-3i_bkjbMPnqmi2t4D8Gl1T1L9KpdFTyR7tXNRSem3k-O4ZP8W7jdx5rukx-qDguo027BEvLunaAOo/s2160/Boland%20F1b%20annotated.jpg" style="clear: left; float: left; margin-bottom: 1em; margin-right: 1em;"><img border="0" data-original-height="668" data-original-width="2160" height="198" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEj5pDDGJscW2FHci08qpcB-QeMp8hyDmkPHUwEfyZpqACNg-6h9Jvr9C6gR8mB5mNOW994DTqzbxj_9kV_Tn7co9h7VcLx4jJbLjjPWn-3i_bkjbMPnqmi2t4D8Gl1T1L9KpdFTyR7tXNRSem3k-O4ZP8W7jdx5rukx-qDguo027BEvLunaAOo/w640-h198/Boland%20F1b%20annotated.jpg" width="640" /></a></span></div><span style="font-size: small;"><br /></span><span style="font-family: arial;"><span style="font-size: small;"><a href="https://en.wikipedia.org/wiki/Granulin" target="_blank">Granulins</a> are a family of secreted, glycosylated peptides (A, B, C, <i>etc</i>.)
cleaved from a single precursor (progranulin, PGRN), that are involved
in a wide range of activities probably due to their roles in regulating
protein lysosomal protein metabolism.
The authors of this study found that <a href="https://en.wikipedia.org/wiki/Ganglioside " target="_blank">gangliosides</a> (<i>i.e</i>.,
glycosphingolipids with attached sialic acids)
are elevated in brains of granulin mutant mice (GRN R504X), which are analogous to the most
prevalent granulin mutation in humans, R493X (substitution of the
arginine normally at position 493 with a nonsense codon, resulting in a
truncated protein). This mutation causes neuronal ceroid
lipofuscinosis, a severe neurodevelopmental disease, in humans and
neuroinflammation in mice (<a href="https://www.jax.org/strain/029919" target="_blank">Jax</a>).
The metabolic order in the ganglioside degradation pathway (Fig. 1a) is
first disialylated GD1 (Fig. 1b, shown, rightmost plot, annotated with
red #1) 👉 monosialylated GM1 (#2) 👉 GM2 (#3) 👉 GM3. Also, GD2 👉
GM3 (#3’) via a</span></span><span style="font-family: arial;"><span style="font-size: small;">n alternative pathway. Levels of precursor GD1 (#1) are significantly elevated in the brains of mice with heterozygous mutant granulin (Figure 1b: blue fill, Grn +/R493X) compared with normal granulin (Grn+/+, grey) but not in homozygous mutants (purple). This may suggest a feed-back mechanism that limits the accumulation of that metabolite. GM1, #2, is elevated in homozygous mutant brain compared to normal, with the heterozygous mutant intermediate. However, GM2, #3, is not significantly elevated in mutation-bearing mouse brains. The alternate pathway, #3’, shows elevated GD3, the precursor to GM3, in homozygous mutant brains. </span></span><p></p><p><span style="font-family: arial;"><span style="font-size: small;">They also analyzed the lipids in postmortem human brains of 12 GRN mutation-related FTD cases, 6 sporadic FTD cases, and 3 control normal subjects. GD3 and GM1 are significantly elevated in GRN-related FTD cases (Fig 1c, blue columns). However, they both seem also elevated in non-GRN (sporadic) FTD cases (green). GD1 is significantly elevated in GRN-related but not -unrelated FTD. </span></span></p><p><span style="font-family: arial;"><span style="font-size: small;">In a striking simplification, they tested the effects of removing the granulin precursor protein gene, <a href="https://www.ncbi.nlm.nih.gov/gene/2896" target="_blank">PGRN</a> (same as GRN), in HeLa cells (Fig 2). They found elevated GM2 in the deficient line (GRN-/-) that was reduced to normal levels by restoring granulin (GRN-/- + PGRN-addback). </span></span></p><p><span style="font-family: arial;"><span style="font-size: small;">What causes changes in the levels of gangliosides? Gangliosides are catabolized by lysosomal enzymes. However, those enzymes were not altered by GRN deficiency (Fig 3). An intermediate metabolite, bis(monoacylglycero)phosphate (BMP), which is crucial to ganglioside degradation, was found to be reduced by 50-60% in GRN-deficient HeLa cells and mouse brains, and ‘markedly’ in human brains of FTD cases, although again both GRN-related and sporadic cases (Fig 4d). The authors propose a model wherein “lysosomal granulin peptides maintain lysosomal function and homeostasis, including the levels of BMP, that are crucial for ganglioside catabolism”. Their results await confirmation by others and many details remain to be pursued further. One relatively simple aspect will be clarifying how the model accounts for <a href="https://omim.org/entry/607485" target="_blank">autosomal dominance</a> of GRN deficiency. Also worth noting is the proximity of <a href="https://en.wikipedia.org/wiki/Granulin" target="_blank">GRN</a> and the Alzheimer- and Parkinson-associated <a href="https://en.wikipedia.org/wiki/Tau_protein" target="_blank">MAPT</a> genes, within a million nucleotides in band 17q21.31. </span></span></p><p><span style="font-family: arial;"><span style="font-size: small;"></span></span></p><div class="separator" style="clear: both; text-align: center;"><span style="font-size: small;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEh73_kG1w3pkkpXeZGKnq5YIYGu99j0L6F70dbZRf4O2S1SaAv16kvKPoCYADSYFxaMiyMsZ3fm252ykoAa1haXQhUBfmGjSMxZIGChxV1bJURZO8X8GBBrh4ekb4eDnxF_2bv6RJEgaCo-HuyXGWGb7mRjlZvjGadsuqUVkYVRdmBvkx3XsCQ/s322/OpenAccessIcon.jpg" style="clear: left; float: left; margin-bottom: 1em; margin-right: 1em;"><img border="0" data-original-height="322" data-original-width="200" height="100" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEh73_kG1w3pkkpXeZGKnq5YIYGu99j0L6F70dbZRf4O2S1SaAv16kvKPoCYADSYFxaMiyMsZ3fm252ykoAa1haXQhUBfmGjSMxZIGChxV1bJURZO8X8GBBrh4ekb4eDnxF_2bv6RJEgaCo-HuyXGWGb7mRjlZvjGadsuqUVkYVRdmBvkx3XsCQ/w62-h100/OpenAccessIcon.jpg" width="62" /></a></span></div><span style="font-size: small;">Boland S, Swarup S, Ambaw YA, Malia PC, Richards RC, Fischer AW, Singh S, Aggarwal G, Spina S, Nana AL, Grinberg LT, Seeley WW, Surma MA, Klose C, Paulo JA, Nguyen AD, Harper JW, Walther TC, Farese RV Jr. <i><a href="https://www.nature.com/articles/s41467-022-33500-9 " target="_blank">Deficiency of the frontotemporal dementia gene GRN results in gangliosidosis</a></i>. Nat Commun. 2022 Oct 7;13(1):5924. doi: 10.1038/s41467-022-33500-9. PMID: 36207292; PMCID: PMC9546883. </span><p></p>Unknownnoreply@blogger.com0tag:blogger.com,1999:blog-32683882.post-27849837201165271912022-10-06T04:36:00.002-05:002022-10-06T04:43:16.187-05:00COVID restrictions – Moderation is good<p class="MsoNormal" style="margin: 0in;"><span style="font-family: arial;">In efforts to reduce the spread of COVID-19, billions of people around the world were subject to rules and laws governing their behavior. Among the various non-pharmaceutical interventions (NPIs), what worked? </span></p><p class="MsoNormal" style="margin: 0in;"><span style="font-family: arial;"><o:p></o:p></span></p><p class="MsoNormal" style="margin: 0in;"><o:p><span style="font-family: arial;"> </span></o:p></p><p class="MsoNormal" style="margin: 0in;"><span style="font-family: arial;">An influential early report analyzing data from 11 European countries during the first 4 months of the pandemic found that lockdowns reduced transmission rates (Rt values) significantly, ~80%, whereas other NPIs such as cancelling public events, school closure, encouraging social distancing, and self-isolation, resulted in less significant reductions (0-20%) (Fig 2, <a href="https://www.nature.com/articles/s41586-020-2405-7" target="_blank">Flaxman</a>). The dramatic drop in infections after lockdown is so obvious that it required no modeling (Fig 1). A similar study found the most effective NPIs for lowering cases were travel restrictions, school closures, and the partial lockdown (<a href="https://archpublichealth.biomedcentral.com/articles/10.1186/s13690-022-00830-5" target="_blank">Cortis</a>). A related study of 19 NPIs during seasonal flu found that banning large gatherings was most effective in limiting transmission (<a href="https://bmcinfectdis.biomedcentral.com/articles/10.1186/s12879-022-07317-2#MOESM1" target="_blank">Qiu</a>). These studies used epidemiological models that directly involve underlying mechanisms.</span></p><p class="MsoNormal" style="margin: 0in;"><span style="font-family: arial;"><o:p></o:p></span></p><p class="MsoNormal" style="margin: 0in;"><o:p><span style="font-family: arial;"> </span></o:p></p><p class="MsoNormal" style="margin: 0in;"><span style="font-family: arial;">Data on cases, deaths, vaccinations, and tests, were obtained from the <a href="https://covid19datahub.io" target="_blank">COVID-19 Data Hub</a> (<a href="https://www.nature.com/articles/s41597-022-01245-1" target="_blank">Guidotti</a>). NPI data were obtained from the Oxford Covid-19 Government Response Tracker (<a href="https://www.bsg.ox.ac.uk/research/research-projects/covid-19-government-response-tracker" target="_blank">OxCGRT</a>). </span></p><p class="MsoNormal" style="margin: 0in;"><o:p><span style="font-family: arial;"> </span></o:p></p><p class="MsoNormal" style="margin: 0in;"><span style="font-family: arial;">In this report, the author analyzed data from 132 countries between Feb 2020 to April 2021, capturing 3 waves of infection, beginning March 202, July 2020, and January 2021. An econometric model with 4 equations: C = cases growth rate, D= deaths growth rate, M = mobility, and p(SI) = probability of the assigned stringency intensity level was employed. Stringency correlates inversely with nonresidential mobility (Fig 3). He found that ‘unobserved variables’ influence the growth of cases and deaths (C and D) as well as the stringency (SI) of government policies. <b>Medium-stringency measures greatly reduced case and death growth rates but, surprisingly, yet-more-stringent measures slightly increased them</b> (Fig. 4, shown). </span><span style="font-family: arial;"> </span></p><p class="MsoNormal" style="margin: 0in;"><table cellpadding="0" cellspacing="0" class="tr-caption-container" style="float: left;"><tbody><tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEh6gENwsRlPG8yTk78OSx60DgG4IoYDqfEQWKVu6ujlYtgZq4CVFASQVSdgBw3KwyG9L044DX47JxWNsrdHvSUaMrssAjfzmA5-roe66Phf-OwjzX1AmFsK-wn34NnNZhAfYkgJIrOiHcW5sYZ0m1XCHeFY6gRcANf5fFK_13NQK1Hfs37bjAA/s2446/F4%20C-DvSI.jpg" imageanchor="1" style="clear: left; margin-bottom: 1em; margin-left: auto; margin-right: auto;"><span style="font-family: arial;"><img border="0" data-original-height="1002" data-original-width="2446" height="264" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEh6gENwsRlPG8yTk78OSx60DgG4IoYDqfEQWKVu6ujlYtgZq4CVFASQVSdgBw3KwyG9L044DX47JxWNsrdHvSUaMrssAjfzmA5-roe66Phf-OwjzX1AmFsK-wn34NnNZhAfYkgJIrOiHcW5sYZ0m1XCHeFY6gRcANf5fFK_13NQK1Hfs37bjAA/w640-h264/F4%20C-DvSI.jpg" width="640" /></span></a></td></tr><tr><td class="tr-caption" style="text-align: center;"><span style="font-family: arial;"><span style="text-align: left;">Fig. 4 Case (panel a) and Death (panel b) growth rates vs NPI Stringency Index.</span><span style="text-align: left;"> <br /></span></span></td></tr></tbody></table><span style="font-family: arial;"><br /></span></p><p class="MsoNormal" style="margin: 0in;"><span style="font-family: arial;"><br /></span></p><p class="MsoNormal" style="margin: 0in;"><span style="font-family: arial;"><br /></span></p><p class="MsoNormal" style="margin: 0in;"><span style="font-family: arial;"><br /></span></p><p class="MsoNormal" style="margin: 0in;"><span style="font-family: arial;"><br /></span></p><p class="MsoNormal" style="margin: 0in;"><span style="font-family: arial;"><br /></span></p><p class="MsoNormal" style="margin: 0in;"><span style="font-family: arial;"><br /></span></p><p class="MsoNormal" style="margin: 0in;"><span style="font-family: arial;"><br /></span></p><p class="MsoNormal" style="margin: 0in;"><span style="font-family: arial;"><br /></span></p><p class="MsoNormal" style="margin: 0in;"><span style="font-family: arial;"><br /></span></p><p class="MsoNormal" style="margin: 0in;"><span style="font-family: arial;"><br /></span></p><p class="MsoNormal" style="margin: 0in;"><span style="font-family: arial;"><br /></span></p><p class="MsoNormal" style="margin: 0in;"><span style="font-family: arial;"><br /></span></p><p class="MsoNormal" style="margin: 0in;"><span style="font-family: arial;"><br /></span></p><p class="MsoNormal" style="margin: 0in;"><span style="font-family: arial;"><br /></span></p><p class="MsoNormal" style="margin: 0in;"><span style="font-family: arial;"><br /></span></p><p class="MsoNormal" style="margin: 0in;"><span style="font-family: arial;">Testing helped but contact tracing did little (Fig 5). The benefits of reduced nonresidential mobility were outweighed by increased within-household transmission. </span><span style="font-family: arial;">Various differences in culture, compliance, and enforcement of government imposed NPIs were acknowledged but not clearly managed.</span><span style="font-family: arial;"> </span><span style="font-family: arial;">Even low levels of vaccination reduced Case and Death growth rates with nonlinear improvement anticipated. </span></p><p class="MsoNormal" style="margin: 0in;"><span style="font-family: arial;"><br /></span></p><p class="MsoNormal" style="margin: 0in;"><span style="font-family: arial;">The findings disagree with previous reports that lockdowns are effective, concluding that "very stringent NPIs provide no further benefits over moderately stringent ones, and that less stringent NPIs function primarily as signals for significant voluntary changes in citizens’ behavior.". Such analyses are crucial for designing effective, results-driven policies and for persuading people to comply. </span></p><p class="MsoNormal" style="margin: 0in;"><span style="font-family: arial;"><o:p></o:p></span></p><p class="MsoNormal" style="margin: 0in;"><o:p><span style="font-family: arial;"> </span></o:p></p><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEicKQmVbEoDKgHmJn-NKqg41b8eBbiVvuGkjFoKMINR1dJWankZe1VHleqfbSS75swS6JAdnTh_OlZFtybHl1HkVjCv34GCQerxpP2-g1xm4-jNma_g9paQ1cOToV_ZHWRsqaNgDfKEz4Lg5kofRvKB0YnMVOgBm8cJJzoGw-HXOOKiMdDoJqs/s468/PubMedGov.jpg" imageanchor="1" style="clear: left; float: left; margin-bottom: 1em; margin-right: 1em;"><span style="font-family: arial;"><img border="0" data-original-height="134" data-original-width="468" height="58" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEicKQmVbEoDKgHmJn-NKqg41b8eBbiVvuGkjFoKMINR1dJWankZe1VHleqfbSS75swS6JAdnTh_OlZFtybHl1HkVjCv34GCQerxpP2-g1xm4-jNma_g9paQ1cOToV_ZHWRsqaNgDfKEz4Lg5kofRvKB0YnMVOgBm8cJJzoGw-HXOOKiMdDoJqs/w200-h58/PubMedGov.jpg" width="200" /></span></a></div><p class="MsoNormal" style="margin: 0in;"><span style="font-family: arial;">Spiliopoulos L. <a href="https://pubmed.ncbi.nlm.nih.gov/36183075/ https://bmcpublichealth.biomedcentral.com/articles/10.1186/s12889-022-14177-7" target="_blank">On the effectiveness of COVID-19 restrictions and lockdowns: Pan metron ariston</a>. BMC Public Health. 2022 Oct 1;22(1):1842. doi: 10.1186/s12889-022-14177-7. PMID: 36183075; PMCID: PMC9526209.</span></p><p class="MsoNormal" style="margin: 0in;"><span style="font-family: arial;"><o:p></o:p></span></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;"><br /></p>Unknownnoreply@blogger.com0tag:blogger.com,1999:blog-32683882.post-85190194299125440742022-09-28T07:54:00.004-05:002022-09-28T07:59:39.534-05:00Antibody specificities are Gut reactions <div style="text-align: left;"><span style="font-family: inherit;"><span face="Calibri, sans-serif"><a href="https://en.wikipedia.org/wiki/Germ-free_animal" target="_blank">Germ-free (GF) mice</a></span><span face="Calibri, sans-serif"> </span><span face="Calibri, sans-serif">have undeveloped immune systems and practically no antibodies.</span><span face="Calibri, sans-serif"> </span><span face="Calibri, sans-serif"> </span><span face="Calibri, sans-serif">How do <a href="https://en.wikipedia.org/wiki/Microbiota#Gut_microbiota_development_and_antibiotics" target="_blank">microbes in the gut</a></span><span face="Calibri, sans-serif"> </span><span face="Calibri, sans-serif">(gastro-intestinal tract) stimulate immunity?</span><span face="Calibri, sans-serif"> </span><span face="Calibri, sans-serif"> </span><span face="Calibri, sans-serif">This group looked at the specificity of antibodies that develop after GF mice are colonized by individual <a href="https://www.ncbi.nlm.nih.gov/books/NBK8406/" target="_blank">bacterial species and strains</a></span><span face="Calibri, sans-serif"> </span><span face="Calibri, sans-serif">(monocolonization).</span><span face="Calibri, sans-serif"> </span><span face="Calibri, sans-serif"> </span><span face="Calibri, sans-serif">They used 8 strains of bacteria to inoculate GF mice and, after 3 weeks, analyzed the specificity of antibodies produced in the gut (recovered from fecal matter) and blood, focusing on the <a href="https://en.wikipedia.org/wiki/Immunoglobulin_A" target="_blank">IgA isotype</a></span><span face="Calibri, sans-serif"> </span><span face="Calibri, sans-serif">that protects mucosal surfaces.</span><span face="Calibri, sans-serif"> </span><span face="Calibri, sans-serif"> </span></span></div><p><span face="Calibri, sans-serif"></span></p><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgba7nCgQLAbDyDoiLCNANkYXk1WdOn99LBbVUImvpHj1BO1Kao2q0kQPa0fsW-5_s6MHnkRVF2XC0hlBw75EOBbJfVZBseZy2BZJ7GwVFXiKAlTsZ1i78Mp0M0cW2_Rjt2bMgUvV68eith5MqbpA2JtHoAcy59rQy7sdbF64zwMAswyliNuBc/s2496/F1a%20Yang%20IgA-sp.jpg" style="clear: left; float: left; margin-bottom: 1em; margin-left: 1em;"><img border="0" data-original-height="1388" data-original-width="2496" height="224" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgba7nCgQLAbDyDoiLCNANkYXk1WdOn99LBbVUImvpHj1BO1Kao2q0kQPa0fsW-5_s6MHnkRVF2XC0hlBw75EOBbJfVZBseZy2BZJ7GwVFXiKAlTsZ1i78Mp0M0cW2_Rjt2bMgUvV68eith5MqbpA2JtHoAcy59rQy7sdbF64zwMAswyliNuBc/w400-h224/F1a%20Yang%20IgA-sp.jpg" width="400" /></a></div><span style="font-family: inherit;">Not surprisingly, the antibodies tend to bind specifically to those strains of microbes against which they were stimulated (shown, Figure 1, panel A). They also found that mice monocolonized from birth produce more IgA reactive with that species (termed ‘self’) than newly-introduced species. They make a point about IgA being able to ‘aggregate pathogenic bacteria’ and ‘selectively coat disease-associated bacteria’ but it is unclear how IgA itself could distinguish dangerous from benign and anyway they tested only benign bacteria.<span face="Calibri, sans-serif"> </span></span><p></p><p><span style="font-family: inherit;"><span face="Calibri, sans-serif">A small panel (29) of monoclonal IgA antibodies cloned from gut tissues of monocolonized mice also showed species specificity. Finally, they showed that monoclonal IgA antibodies with specific binding activity could be detected in the feces of mice that had been force-fed the IgA 3 hours previously, suggesting a targeted, potential therapy (e.g., against the human pathogen</span><span face="Calibri, sans-serif"> </span><i>Clostridioides difficile</i><span face="Calibri, sans-serif">). </span></span></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;"><o:p></o:p></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;"><o:p></o:p></p><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEh3JOv_oZejjG2CxcpVKBsy8GrCFvfpoevJliqUqU_69gErmwF9NSaLnGG8UWsgth7Rv0C1qhemk_L9JcUvwEp3wWbPINvknRwqEpKlTqbnKZ8u9xJTMUq76ebw3AyALhgJhtCl-4fD1l6_kJh1qUfBgxHfby_yCmTy0Cus8MA5ejS18XJbmzc/s468/PubMedGov.jpg" style="clear: left; float: left; margin-bottom: 1em; margin-left: 1em;"><img border="0" data-original-height="134" data-original-width="468" height="58" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEh3JOv_oZejjG2CxcpVKBsy8GrCFvfpoevJliqUqU_69gErmwF9NSaLnGG8UWsgth7Rv0C1qhemk_L9JcUvwEp3wWbPINvknRwqEpKlTqbnKZ8u9xJTMUq76ebw3AyALhgJhtCl-4fD1l6_kJh1qUfBgxHfby_yCmTy0Cus8MA5ejS18XJbmzc/w200-h58/PubMedGov.jpg" width="200" /></a></div>Yang C, Chen-Liaw A, Spindler MP, Tortorella D, Moran TM, Cerutti A, Faith JJ. <a href="https://pubmed.ncbi.nlm.nih.gov/35857580/" target="_blank">Immunoglobulin A antibody composition is sculpted to bind the self gut microbiome</a>. ScienceImmunology. 2022 Jul 15;7(73) <p></p>Unknownnoreply@blogger.com0tag:blogger.com,1999:blog-32683882.post-35119785831893143592022-09-21T13:56:00.004-05:002022-09-21T13:56:55.210-05:00Covid Vax vs Variants<p style="text-align: left;"><span style="font-family: arial;">The first RNA vaccines against Covid were based on the <a href="https://www.ncbi.nlm.nih.gov/gene/43740568/" target="_blank">Surface, S</a> or “Spike” protein from the <a href="https://www.ncbi.nlm.nih.gov/data-hub/taxonomy/2697049/">reference genome</a> of SARS-CoV-2, Wuhan-Hu-1, published in January 2020. Since then, more-infectious variants have emerged; one, <a href="https://pubmed.ncbi.nlm.nih.gov/33106671/" target="_blank">D614G</a>, dominated but did not escape vaccine protection probably because its characteristic mutation is located outside the Receptor Binding Domain (RBD, 319-541). In the past year, delta variants were <a href="https://nextstrain.org/ncov/gisaid/global/6m" target="_blank">overtaken by omicron variants</a>, which have numerous changes in the RBD, raising concern that they escape current RNA vaccines. </span></p><p style="text-align: left;"><span style="font-family: arial;">Neutralization assays measure the ability of blood-borne antibodies to block viral infection of cells grown in a culture dish; they are thought to provide valid measurements of protection. These authors previously tested Covid neutralization with blood sera from 15 health care workers, 4 vaccinated with Moderna (mRNA-1273) and 11 with Pfizer-BioNTech (BNT162b2). They confirmed that <a href="https://www.nejm.org/doi/full/10.1056/NEJMc2206725" target="_blank">a third dose (second booster) increased the neutralization activity</a> (titer) against all strains, albeit 3-4 times weaker against subvariants compared with the ancestral version. Moreover, they showed the neutralization titers induced by 3 doses of the vaccines, and therefore presumably levels of protection provided, approximated those found in convalescent (sick) Covid patients (Fig 1 panel B vs C and D). </span></p><p style="text-align: left;"></p><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiL-HXoNZ93aq7prFHvHbb3nBNxfWz8Mn0qGQaxE562k2y-fdho-7puXE--HRLwBMJAelUOyk16PzOS-zUOeTz0fUl7-Em28khhU6lt9fw63up0u_2gb2_aBYjZ3R-wAk0SQpSsHnAz2kNdS9-f3S7uowTUjqhVQwfIViurjNeeGLnmmRNI3dQ/s2350/F1c%20Decay.jpg" imageanchor="1" style="clear: left; float: left; margin-bottom: 1em; margin-right: 1em;"><img border="0" data-original-height="1162" data-original-width="2350" height="198" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiL-HXoNZ93aq7prFHvHbb3nBNxfWz8Mn0qGQaxE562k2y-fdho-7puXE--HRLwBMJAelUOyk16PzOS-zUOeTz0fUl7-Em28khhU6lt9fw63up0u_2gb2_aBYjZ3R-wAk0SQpSsHnAz2kNdS9-f3S7uowTUjqhVQwfIViurjNeeGLnmmRNI3dQ/w400-h198/F1c%20Decay.jpg" width="400" /></a></div><span style="font-family: arial;">In this letter, they studied 46 health care workers, 24 vaccinated and boosted with Moderna and 22 with Pfizer-BioNTech. Fourteen of the cohort were infected during the follow-up year. Figure S3 in the supplementary data confirm the protection provided by a third dose (second booster). They found that neutralization titers against all strains declined over time. Titers from vaccinated people remained within a substantial fraction of those from infected people (shown, dashed vs solid lines). </span><p></p><p style="text-align: left;"><span style="font-family: arial;">How much protection -- neutralization titer -- is enough? A paper published last year analyzing 7 different vaccines reported that <a href="https://www.nature.com/articles/s41591-021-01377-8" target="_blank">neutralization titers are predictive of protection</a>. Neutralization titers of 20% of convalescent levels protected on average half of people against detectable infection; levels at 3% convalescent protected against severe Covid. Taken together, these results seem to support the value of the ‘old’ vaccines against the newer variants. </span></p><p style="text-align: left;"><span style="font-family: arial;"></span></p><div class="separator" style="clear: both; text-align: center;"><span style="font-family: arial;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEixy5KqNcBKDdcPvIzP5n9a58SVXKuVgE6Zj5RWeax8nggvCv0cOEmFhGx0ZSsKJEXCanKLAWjSVeRpS14RPX_TBPaxxtJMGL61rziCPKsTEEfiRG4bES4wnvaqPCQ7KAU-V02VgZM72y6pBdlIc62yTRDHH8ev_-D3TVgAZxr6JZxUCMGyWAg/s468/PubMedGov.jpg" imageanchor="1" style="clear: left; float: left; margin-bottom: 1em; margin-right: 1em;"><img border="0" data-original-height="134" data-original-width="468" height="58" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEixy5KqNcBKDdcPvIzP5n9a58SVXKuVgE6Zj5RWeax8nggvCv0cOEmFhGx0ZSsKJEXCanKLAWjSVeRpS14RPX_TBPaxxtJMGL61rziCPKsTEEfiRG4bES4wnvaqPCQ7KAU-V02VgZM72y6pBdlIc62yTRDHH8ev_-D3TVgAZxr6JZxUCMGyWAg/w200-h58/PubMedGov.jpg" width="200" /></a></span></div><span style="font-family: arial;">Qu P, Faraone JN, Evans JP, Zheng YM, Yu L, Ma Q, Carlin C, Lozanski G, Saif LJ, Oltz EM, Gumina RJ, Liu SL. <a href="https://pubmed.ncbi.nlm.nih.gov/36069925/" target="_blank">Durability of Booster mRNA Vaccine against SARS-CoV-2 BA.2.12.1, BA.4, and BA.5 Subvariants</a>. N Engl J Med. 2022 Sep 7. </span><p></p>Unknownnoreply@blogger.com1tag:blogger.com,1999:blog-32683882.post-69262040608674131872022-09-13T11:18:00.000-05:002022-09-13T11:18:10.209-05:00Obesity and severe COVID<p><span style="font-family: inherit;">Early in the <a href="https://en.wikipedia.org/wiki/COVID-19_pandemic" target="_blank">COVID-19 pandemic</a>, it was recognized that obesity seemed to be related to respiratory failure, or severe acute respiratory syndrome (<a href="https://en.wikipedia.org/wiki/SARS" target="_blank">SARS</a>). These researchers tested whether <a href="https://en.wikipedia.org/wiki/Leptin" target="_blank">leptin</a>, a cytokine produced by fat cells in the gut and working on brain cells to influence hunger, might be correlated with risk, perhaps a biomarker of risk. </span></p><p class="MsoNormal" style="margin: 0in;"><span style="font-family: inherit;"><o:p></o:p></span></p><p class="MsoNormal" style="margin: 0in;"><span style="font-family: inherit;">They compared 31 obese COVID patients on ventilators with 8 non-infected, non-obese critically ill patients. They found much higher levels of leptin in the patients with COVID (averages 21 vs 6 ug/l, with very good statistical significance, p = .0007). The individual measurements overlap (shown), so leptin is not ‘the’ biomarker but clearly related. Whether related as a cause or consequence only a prospective trial could test rigorously. </span></p><p class="MsoNormal" style="margin: 0in;"></p><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEirBp4Wwyn1RvyqbGv3LVkH2PUitc-U-t9E698nrZ_IXBxdLwrbwjWjiiJvq77u55cLiqw4hBY75lxqEww-qXXpliOcUL8shxSMG8UDZuaJMTWsTNuCiQiVM9Svg3ct-jDzZ4Nk1w4TmULgDsuH6sBd_Uu0GCjrdblPKo0JMwhDFVy1vsbFSNo/s1386/Fig2ab%20leptin.jpg" style="clear: left; float: left; margin-bottom: 1em; margin-right: 1em;"><span style="font-family: inherit;"><img border="0" data-original-height="1144" data-original-width="1386" height="264" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEirBp4Wwyn1RvyqbGv3LVkH2PUitc-U-t9E698nrZ_IXBxdLwrbwjWjiiJvq77u55cLiqw4hBY75lxqEww-qXXpliOcUL8shxSMG8UDZuaJMTWsTNuCiQiVM9Svg3ct-jDzZ4Nk1w4TmULgDsuH6sBd_Uu0GCjrdblPKo0JMwhDFVy1vsbFSNo/w320-h264/Fig2ab%20leptin.jpg" width="320" /></span></a></div><p></p><p class="MsoNormal" style="margin: 0in;"><span style="font-family: inherit;">Figure 2 detail: BMI of patients panel A and Leptin levels panel B. In each panel, ‘control’ critically ill patients, left, COVID patients right. <o:p></o:p></span></p><p class="MsoNormal" style="margin: 0in;"><o:p><span style="font-family: inherit;"> </span></o:p></p><p class="MsoNormal" style="margin: 0in;"><span style="font-family: inherit;"><span>The authors hypothesized that elevated leptin causes a ‘hyper immune’ state, especially stimulating lung epithelial cells. They noted similar observation previously published for influenza and MERS. Since this paper was published, several groups have reported similar findings 2020 paper that was largely replicated (see <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9002648/" target="_blank">review</a>, which cites 3 later papers). Ironically, shutdowns that have been effective in protecting many people from infection have also increased sedentary </span><span face="Calibri, sans-serif">lifestyles, BMI, and risk. <o:p></o:p></span></span></p><p class="MsoNormal" style="margin: 0in;"><o:p><span style="font-family: inherit;"> </span></o:p></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;"><o:p></o:p></p><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEj1v5v1WpGngkO8TFUN_AnN5dveQb00qM5O3tMDjoLPQIEh848WICM36V61twtTxuCcnjrFQ8VcR7ofqWpXDuX0i0BBFVJCqDKi_FQvuOD1kaWiF2gqPA0B9JYX0w9avbpruUK5rOIelkJQ2z98qKUu-gCyig-lo_546zfTOzLMdvZilHc8d30/s154/Heliyon.jpg" style="clear: left; float: left; margin-bottom: 1em; margin-right: 1em;"><img border="0" data-original-height="72" data-original-width="154" height="94" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEj1v5v1WpGngkO8TFUN_AnN5dveQb00qM5O3tMDjoLPQIEh848WICM36V61twtTxuCcnjrFQ8VcR7ofqWpXDuX0i0BBFVJCqDKi_FQvuOD1kaWiF2gqPA0B9JYX0w9avbpruUK5rOIelkJQ2z98qKUu-gCyig-lo_546zfTOzLMdvZilHc8d30/w200-h94/Heliyon.jpg" width="200" /></a></div><span face="Calibri, sans-serif" style="font-family: inherit; font-size: 12pt;">van der Voort PHJ, Moser J, Zandstra DF, Muller Kobold AC, Knoester M, Calkhoven CF, Hamming I, van Meurs M. <a href="https://www.cell.com/heliyon/fulltext/S2405-8440(20)31539-5?_returnURL=https%3A%2F%2Flinkinghub.elsevier.com%2Fretrieve%2Fpii%2FS2405844020315395%3Fshowall%3Dtrue" target="_blank">Leptin levels in SARS-CoV-2 infection related respiratory failure: A cross-sectional study and a pathophysiological framework on the role of fat tissue</a>. Heliyon. 2020 Aug;6(8):</span>Unknownnoreply@blogger.com0tag:blogger.com,1999:blog-32683882.post-19986942412956199142022-09-07T09:59:00.002-05:002022-09-28T07:48:57.745-05:00A kidney ‘punch’ can tell much <div><p style="text-align: left;"><span style="font-family: arial;">A <a href="https://en.wikipedia.org/wiki/Renal_biopsy" style="color: #954f72;" target="_blank">renal biopsy</a> is when a small piece of a patient's kidney is removed for analysis, usually by inserting a needle through the skin and into the kidney. Though invasive, the clinical value can be high for helping decide how to treat lupus or transplanted patients. How to maximize that value? </span></p>
<p class="MsoNormal" style="margin: 0in; text-align: left;"><span style="font-family: arial;">In this study, Clark and colleagues applied computer imaging techniques to answer why only about half of lupus patients with inflamed kidneys (nephritis) proceed to kidney failure (<a href="https://en.wikipedia.org/wiki/Kidney_failure" style="color: #954f72;" target="_blank">end stage renal disease</a>, ESRD) and lose their kidney. They supposed there were subtle differences in the “frequency and organization of principal cellular effectors” between those patients who did, or didn’t, progress. They obtained biopsies from a cohort of 55 well-characterized lupus patients, of which 19 progressed to ESRD. They labeled very thin slices (sections) of kidney with 6 markers (CD3, CD4, CD20, CD11c, BDCA2, and DAPI) and counted several types of immune cells using confocal microscopy and deep learning analysis. </span></p><p class="MsoNormal" style="margin: 0in;"></p><table align="center" cellpadding="0" cellspacing="0" class="tr-caption-container" style="float: left; margin-right: 1em; text-align: left;"><tbody><tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiasXTg9sN-7ULaLi_sobXbauxeyT_JGga53OWcF4FQvN_yZytMPwqW0N1kHaaMxxtl8ANl8jRwuFtAjTL7yPoydTtRXubQd6CT9V829AmrByu2F2lj2sAZ1u6Z2jZLbzdE9OtmdgrqQ63szSCIu1A5tmv_5jSi5oUu7ZUw4DWx2HPi5gmmtvU/s610/Fig2%20H-I.jpg" style="margin-left: auto; margin-right: auto;"><img border="0" data-original-height="281" data-original-width="610" height="184" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiasXTg9sN-7ULaLi_sobXbauxeyT_JGga53OWcF4FQvN_yZytMPwqW0N1kHaaMxxtl8ANl8jRwuFtAjTL7yPoydTtRXubQd6CT9V829AmrByu2F2lj2sAZ1u6Z2jZLbzdE9OtmdgrqQ63szSCIu1A5tmv_5jSi5oUu7ZUw4DWx2HPi5gmmtvU/w400-h184/Fig2%20H-I.jpg" width="400" /></a></td></tr><tr><td class="tr-caption" style="text-align: center;"><b style="font-family: arial; text-align: left;">Figure 2</b><span style="font-family: arial; text-align: left;">: left panel (H) are CD20+ B cells, right panel (I are CD3+CD4- T cells, (probably CD8+?).</span></td></tr></tbody></table><p class="MsoNormal" style="margin: 0in;"><span style="font-family: arial;"><br /></span></p><p class="MsoNormal" style="margin: 0in;"><span style="font-family: arial;">They found a remarkably clear distinction: <b>those with few B cells and many CD4- T cells, probably CD8+, often progress to ESRD</b> (shown in red, panels H and I from figure 2). Patients with many B cells and few CD4- T cells do not progress to ESRD (blue). In the discussion, the authors mention that some clinical trials have targeted exactly those cells that this study indicate may be protective (B cells) or innocuous (CD4+ T cells). A validated "identification, friend or foe" (<a href="https://en.wikipedia.org/wiki/Identification_friend_or_foe" style="color: #954f72;">IFF</a>) system seems a good principle before aiming and firing. <o:p></o:p></span></p><p class="MsoNormal" style="margin: 0in;"><span style="font-family: arial;"><br /></span></p><p class="MsoNormal" style="margin: 0in;"><span style="font-family: arial;"></span></p><div class="separator" style="clear: both; text-align: center;"><span style="font-family: arial;"><a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9246394/" style="clear: left; float: left; margin-bottom: 1em; margin-right: 1em;" target="_blank"><img border="0" data-original-height="35" data-original-width="175" height="35" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiIjkfzzvlJaIVobh1ewmFlgKSnLBBMtx7ZEprFbrAtanz6H8IDq4x8hKQ8iCSh__2ehfn72kJCFe6T3wSF2PikT8xoGnZY-EkeT8hl0LCyO3QknM0v3gDA4XfrAn3l4CYMAj21DPtz-tg5HoFHAjJnDQZR_rlrguHUq9_gWjaTYikLO4TQZv4/s1600/PMCicon.gif" width="175" /></a></span></div><span style="font-family: arial;">Abraham R, Durkee MS, Ai J, Veselits M, Casella G, Asano Y, Chang A, Ko K, Oshinsky C, Peninger E, Giger ML, Clark MR. <i>Specific in situ inflammatory states associate with progression to renal failure in lupus nephritis</i>. J Clin Invest. 2022 Jul 1;132(13)</span></div>Unknownnoreply@blogger.com0tag:blogger.com,1999:blog-32683882.post-54942980322650831292016-02-21T22:22:00.002-05:002016-02-22T09:39:00.780-05:00Skinny Genes: Human Warming and the Reverse Butterfly EffectObesity in humans is associated with a region around <a href="http://omim.org/entry/610966"><i style="mso-bidi-font-style: normal;">FTO</i></a>, a "fat mass and obesity-associated” gene on chromosome 16. Although this is the strongest genetic association, it accounts for only a 1-2% difference in Body Mass Index (BMI) and the mechanism was unknown. Here, the investigators looked at regulator proteins binding to variants DNA sequences within the <i style="mso-bidi-font-style: normal;">FTO</i> region, particularly those binding to sites with single nucleotide polymorphisms (SNPs), in 100 healthy Europeans -- 52 subjects were homozygous for 3 risk-variant SNPs (both alleles, all 3 loci) and the remaining 48 were homozygous for the non-risk variants.<br />
<br />
They found that the change of a T-to-C at one SNP within a risk allele of <i style="mso-bidi-font-style: normal;">FTO</i> prevented the binding of the <a href="http://www.ncbi.nlm.nih.gov/books/NBK26872/#A1298">repressor</a> protein ARID5B. For want of this binding site, the repressor is lost. For want of this repressor, the expression of 2 linked genes doubles: IRX3, located about half a million base pairs (~0.5 Mbp) away, and IRX5, ~1 Mbp away. IRX3 repression made mice
thinner by “increased energy dissipation without a change in physical activity or appetite”, i.e. not changing eating or exercise but rather elevating ‘metabolism’. The doubled expression of IRX3 led to a 5-fold reduction in mitochondrial thermogenesis and a 7-fold difference in brown/white adipose tissue development. (Brown fat is brown because it holds more
mitochondria, little furnaces that burn fat and produce heat.)<br />
<br />
The risk alleles are <i style="mso-bidi-font-style: normal;">causative</i>, and mediate through IRX3 and IRX5, because mimicking the repression of IRX3 or IRX5 in 8 carriers of the risk alleles, but not 10 carriers of the non-risk
allele increased stimulated metabolism (Fig 3D, shown, left panel). And overexpression of IRX3 or IRX5 reduced stimulated metabolism in non-risk allele carriers (because their endogenous genes are repressed) but not in risk allele carriers
(Fig 3D, right panel).<br />
<br />
<a href="https://2.bp.blogspot.com/-W8XY3N3Z0P4/VssUnJ2pVxI/AAAAAAAABXk/Yk966MNIkDU/s1600/F3D.jpg" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" height="440" src="https://2.bp.blogspot.com/-W8XY3N3Z0P4/VssUnJ2pVxI/AAAAAAAABXk/Yk966MNIkDU/s640/F3D.jpg" width="640" /></a>
Figure 3D. Oxygen consumption rate (OCR), basal and stimulated, in cells with risk or non-risk alleles.<br />
<br />
The take-home messages are that the causative SNP can be kilobases away from the genes that mediate the effect (not a huge surprise) and that small risks might develop from relatively big differences in particular developmental and cell biological pathways (reverse butterfly effect: not small-change-to-big-effect but big effect leads to small change (1-2%
BMI)).
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<br />
<a href="https://1.bp.blogspot.com/-y3OCwUF8c9A/VssT8TQY8cI/AAAAAAAABXg/TL2Em5syyQw/s1600/pubmed.gif" imageanchor="1" style="clear: left; float: left; margin-bottom: 1em; margin-right: 1em;"><img border="0" src="https://1.bp.blogspot.com/-y3OCwUF8c9A/VssT8TQY8cI/AAAAAAAABXg/TL2Em5syyQw/s1600/pubmed.gif" /></a>N Engl J Med. 2015 Sep 3;373(10):895-907. “<a href="http://www.ncbi.nlm.nih.gov/pubmed/26287746">FTO Obesity Variant Circuitry and Adipocyte Browning in Humans</a>.” Claussnitzer M, Dankel SN, Kim KH, Quon G, Meuleman W, Haugen C, Glunk V, Sousa IS, Beaudry JL, Puviindran V, Abdennur NA, Liu J, Svensson PA, Hsu YH, Drucker DJ, Mellgren G, Hui CC, Hauner H, Kellis MUnknownnoreply@blogger.com2tag:blogger.com,1999:blog-32683882.post-71371044327148568122015-11-22T17:13:00.003-05:002015-11-22T17:14:50.312-05:00Normalizing T lymphocyte metabolism treats lupus autoimmunity Glucose is metabolized in two pathways to fuel cellular
functions: <a href="https://en.wikipedia.org/wiki/Glycolysis">glycolysis</a>, which splits glucose, yielding little energy but providing pyruvate
and other materials for synthesis, and oxidative <a href="https://en.wikipedia.org/wiki/Cellular_respiration#Aerobic_respiration">phosphorylation</a>, which degrades glucose in the mitochondria and produces ~15-fold
more energy. Glucose uptake is a <a href="http://www.ncbi.nlm.nih.gov/pubmed/18354169">limiting in activated T lymphocytes</a><span style="mso-spacerun: yes;"> th</span>rough <a href="http://www.ncbi.nlm.nih.gov/pubmed/12121659">CD28 costimulation</a>. Glucose metabolism is dysregulated in T lymphocytes of
patients with the autoimmune disease Systemic Lupus Erythematosus (SLE, lupus, <a href="http://www.ncbi.nlm.nih.gov/pubmed/15204090">review</a>). <br />
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These investigators blocked <i style="mso-bidi-font-style: normal;">glycolysis</i> with 2-deoxy-D-glucose (<a href="https://en.wikipedia.org/wiki/2-Deoxy-D-glucose">2DG</a>) and <i style="mso-bidi-font-style: normal;">oxidative phosphorylation</i> with metformin (<a href="https://en.wikipedia.org/wiki/Metformin">Met</a>), and observed that
disease was reduced and even reversed in mice “triple congenic” (TC) with three
lupus-predisposing genetic regions: Sle1-Sle2-Sle3 (<a href="http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3240158/">review</a>). 2DG is glucose with its 2-hydroxl group replaced by a
hydrogen, thereby blocking glycolysis.<span style="mso-spacerun: yes;"> </span>Met is a small molecule that was discovered in 1920s to
reduce blood glucose, probably by interfering with mitochondrial respiration.<span style="mso-spacerun: yes;"> </span>The authors show here that Met reduces
extracellular acidification rate (ECAR) and 2DG reduces oxygen consumption rate
(OCR), both measures of glucose metabolism, in activated T cells (fig. 1). <span style="mso-bidi-font-family: "Times New Roman"; mso-fareast-font-family: "Times New Roman";"><span style="mso-spacerun: yes;"> </span></span>
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<a href="http://3.bp.blogspot.com/-NL6rpW8CeoM/VlI81uMis1I/AAAAAAAABW0/zwSQSL3WKVo/s1600/F4-portion.jpg" imageanchor="1" style="clear: left; float: left; margin-bottom: 1em; margin-right: 1em;"><img border="0" height="512" src="http://3.bp.blogspot.com/-NL6rpW8CeoM/VlI81uMis1I/AAAAAAAABW0/zwSQSL3WKVo/s640/F4-portion.jpg" width="640" /></a></div>
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Anti-nuclear antibodies (ANA), a hallmark of lupus, are particularly
dangerous because they damage glomeruli, the kidney’s filtration units, causing
glomerular nephritis (GN).<span style="mso-spacerun: yes;"> </span>The authors
show a remarkable reduction in ANA and spleen size (fig. 4, panels, C, D and a portion of panel E shown here) as
well as improvement in kidney pathology (fig. 4 panel I)</div>
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Although these metabolism inhibitors are not targeted to pathogenic
T cells, there are no obvious adverse consequences for the animal or even the
immune system.<span style="mso-spacerun: yes;"> </span>Treated mice raise
antibody responses following protein immunization, generating normal levels and
avidities of circulating antibodies (supplemental).<span style="mso-spacerun: yes;"> </span>Perhaps the limiting effect of glucose uptake
by pathogenic, chronically activated T cells make them more sensitive to
inhibition.<span style="mso-spacerun: yes;"> </span>How treatment influences
control of chronic infections (e.g., EBV, CMV) is also worth knowing.<span style="mso-spacerun: yes;"> </span>There was no change in body weight on Met.<span style="mso-spacerun: yes;"> </span></div>
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Testing 2 other mouse models of lupus (NZB/W and chronic graft-vs-host
(cGVH)), they found a mixture of responses. <span style="mso-spacerun: yes;"> </span>For example, in cGVH, combined treatment
doesn’t reduce spleens (though Met alone does), while treatment of NZB/W mice reduces
ANA but doesn’t improve GN.<span style="mso-spacerun: yes;"> </span>Human
patients exhibit a range of symptoms and might also be expected to show a range
of responses.<span style="mso-spacerun: yes;"> </span>This is inspired and
inspiring work that cuts across as many disciplines as it does organ systems
and raises as many questions as hopes.<span style="mso-spacerun: yes;"> </span></div>
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<img border="0" src="http://2.bp.blogspot.com/-4LE4Ko4Bpgg/VlI8-vaetDI/AAAAAAAABW8/jeUbMpbQVCI/s1600/pubmed.gif" /> Y. Yin, S.-C. Choi, Z. Xu, D. J. Perry, H. Seay, B. P.
Croker, E. S. Sobel, T. M. Brusko, L. Morel, Normalization of CD4+ T cell
metabolism reverses lupus. <a href="http://www.ncbi.nlm.nih.gov/pubmed/25673763">Sci. Transl. Med. 7, 274</a>ra18 (2015). </div>
Unknownnoreply@blogger.com0tag:blogger.com,1999:blog-32683882.post-16872124822201743352015-03-15T20:10:00.005-05:002015-03-15T20:10:57.422-05:00Stem Cells: Unstable in Culture <a href="http://en.wikipedia.org/wiki/Stem_cell">Stem Cells</a>
(SC) can differentiate into many different cell types, offering the potential
of replacing failing cells, tissues, or even entire organs with new ones
generated from the patient’s own or related donor SC (National Academy of
Sciences <a href="http://www.ncbi.nlm.nih.gov/books/NBK223197/">Workshop summary</a>).<span style="mso-spacerun: yes;"> </span>To be useful for
therapy in the clinic, it would be necessary to grow and expand SCs in culture.<br />
<br />
The authors explored the proliferation of human embryonic SC
(<b>HESC</b>), which are prepared from disrupted embryos, and the less-controversial human
inducible pluripotent stem cells (<b>hiPSCs</b>), which can be prepared from several
adult tissues, including blood, skin, and fat. <span style="mso-spacerun: yes;"> </span>They obtained 1 HESC line, WA09, from the
WiCell Research Institute and they generated 3 hiPSC lines from fetal dermal
fibroblasts by over-expressing the ‘standard reprogramming factors’ (pluripotency-conferring
genes, transduced <a href="http://www.ncbi.nlm.nih.gov/pubmed/17554338">OCT4/POU5F1, SOX2, KLF4, and MYC</a>).<span style="mso-spacerun: yes;"> </span><br />
<br />
They compared four standard SC culture conditions: with or
without a feeder cell layer and enzymatic or “mechanical” (dissection)
disruption, with 6 replicate cultures per condition, for over 100 “passages”
(transfers to fresh cultures). Previous studies cited here revealed genomic
changes (small duplications) that are not detectable by karyotyping,
particularly on chromosome 12, where the pluripotency-related gene NANOG is
encoded, and chromosome 20, where the survival gene Bcl-xL is encoded.<span style="mso-spacerun: yes;"> </span>In addition to measuring proliferation, telomere
length, pluripotency by teratoma formation, they also analyzed over a million
reference SNPs around the genome and used those SNPs to assess copy number
variation (CNV).<span style="font-family: Arial; font-size: 10.0pt; mso-ansi-language: EN-US; mso-bidi-font-size: 12.0pt; mso-bidi-language: AR-SA; mso-fareast-font-family: "Times New Roman"; mso-fareast-language: EN-US;"> </span><br />
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<a href="http://2.bp.blogspot.com/-RwjWqVH89RU/VQYsnNBK2CI/AAAAAAAABUk/nc-U6PRF_zI/s1600/Fig2-comparisons.jpg" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" src="http://2.bp.blogspot.com/-RwjWqVH89RU/VQYsnNBK2CI/AAAAAAAABUk/nc-U6PRF_zI/s1600/Fig2-comparisons.jpg" height="322" width="640" /></a></div>
<br />
<span style="font-family: Arial; font-size: 10.0pt; mso-ansi-language: EN-US; mso-bidi-font-size: 12.0pt; mso-bidi-language: AR-SA; mso-fareast-font-family: "Times New Roman"; mso-fareast-language: EN-US;">Not surprisingly, <b>genomic changes increased with
time in culture</b>, both in aberration number (A) and total length (B) (Figure 2, shown,
WA09 HESC: left duplications and right deletions).<span style="mso-spacerun: yes;"> </span>The number of aberrations was lowest in
“EcmMech” condition, <i>i.e</i>. cultures without feeder cells (only extracellular
matrix, ECM), and disrupted mechanically (blue line). <span style="mso-spacerun: yes;"> </span>The number and length of aberrations was worst
with MefEnz (green line), cultured with feeder cells (mouse embryo fibroblasts,
Mef) and disrupted enzymatically.<span style="mso-spacerun: yes;"> </span>They
conclude that there is a “need for careful assessment of the effects of culture
conditions on cells intended for clinical therapies”.<span style="mso-spacerun: yes;"> </span></span><br />
<br />
“<a href="http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0118307">Increased Risk of Genetic and Epigenetic Instability in Human Embryonic Stem Cells Associated with Specific Culture Conditions</a>”<span style="mso-spacerun: yes;"> </span>Garitaonandia et al. PLoS One 10(2), February
25, 2015
Unknownnoreply@blogger.com1tag:blogger.com,1999:blog-32683882.post-86282227530316981492015-01-24T22:22:00.001-05:002015-01-25T09:45:02.901-05:00Nurture Immunity: Immune system influenced more by environment than by genes Differences in immune protection presumably explain why some
people exposed to infection resist disease or recover while others
succumb.<span style="mso-spacerun: yes;"> </span>These authors sought to distinguish the influences
of genes and environment on immunity. They compared the cellular and molecular components
of the immune system among 210 <a href="http://en.wikipedia.org/wiki/Twin">twins</a>: 78 monozygotic (MZ, “identical”) and 27
dizygotic (DZ, fraternal) pairs.<span style="mso-spacerun: yes;"> </span>They measured
43 serum proteins and 72 immune cell populations repeatedly and longitudinally
(over time) to assess actual variations and account for technical
variations.<span style="mso-spacerun: yes;"> </span>MZ twins, who have
practically identical genomes, and DZ twins, who share half their genes, are
especially valuable for assessing the relative contributions of “<a href="http://en.wikipedia.org/wiki/Nature_versus_nurture">nature or nurture</a>” (genes or environment) to phenotype. <span style="mso-spacerun: yes;"> </span>Their analysis allowed them to detect as
little as 20% heritability.<span style="mso-spacerun: yes;"> </span><br />
<br />
The levels of <b>few</b> proteins and cell populations are under
strong genetic control, such as interleukin-6 and CD4+ “central memory” T
cells, but <b>most are only weakly heritable or not at all</b> (Fig 1). They found
that a common, chronic infection, by <a href="http://en.wikipedia.org/wiki/Cytomegalovirus">cytomegalovirus</a> (CMV), influences the levels of most (58%) cell populations and
proteins (Fig 5).<span style="mso-spacerun: yes;"> </span>Variation
between twins increased as they age, probably reflecting different
environmental stimuli and <a href="http://en.wikipedia.org/wiki/Epigenetics">epigenetic</a> changes (Fig 4).<span style="mso-spacerun: yes;"> </span>Most intriguing, they correlate the
heritability of response to vaccines to the age of immunization, whereby early childhood vaccines
are highly heritable while vaccines after early adolescence have no detectable heritability
(Table 1, shown below).<span style="mso-spacerun: yes;"> </span><span style="mso-spacerun: yes;"> </span><br />
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<a href="http://2.bp.blogspot.com/-CsQ5JSaobQQ/VMRhJlyBqqI/AAAAAAAABT8/Tztq4e_1OFo/s1600/Table%2B1.jpg" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" src="http://2.bp.blogspot.com/-CsQ5JSaobQQ/VMRhJlyBqqI/AAAAAAAABT8/Tztq4e_1OFo/s1600/Table%2B1.jpg" height="276" width="640" /></a><span style="mso-spacerun: yes;"> </span></div>
<div class="MsoNormal">
<a href="https://2.bp.blogspot.com/-H2pZZwtqQGA/VMRgeWo06bI/AAAAAAAABT0/ZzMA3ryBldE/s1600/pubmed.gif" imageanchor="1" style="clear: left; float: left; margin-bottom: 1em; margin-right: 1em;"><img border="0" src="http://2.bp.blogspot.com/-H2pZZwtqQGA/VMRgeWo06bI/AAAAAAAABT0/ZzMA3ryBldE/s1600/pubmed.gif" /></a></div>
Brodin et al. Cell. 2015 Jan 15;160(1-2):37-47. <a href="http://www.ncbi.nlm.nih.gov/pubmed/25594173">Variation inthe human immune system is largely driven by non-heritable influences</a>.<span style="mso-spacerun: yes;"> </span>
<!-- Blogger automated replacement: "https://images-blogger-opensocial.googleusercontent.com/gadgets/proxy?url=http%3A%2F%2F2.bp.blogspot.com%2F-H2pZZwtqQGA%2FVMRgeWo06bI%2FAAAAAAAABT0%2FZzMA3ryBldE%2Fs1600%2Fpubmed.gif&container=blogger&gadget=a&rewriteMime=image%2F*" with "https://2.bp.blogspot.com/-H2pZZwtqQGA/VMRgeWo06bI/AAAAAAAABT0/ZzMA3ryBldE/s1600/pubmed.gif" -->Unknownnoreply@blogger.com3tag:blogger.com,1999:blog-32683882.post-10869842437596240402013-12-08T22:21:00.002-05:002014-02-04T14:55:20.238-05:00Levels of a common, chronic virus (TTV) reflects the immune competence of transplant recipients Successful organ transplantation requires careful immune
suppression: enough to block the rejection of transplant while permitting host defense
against infectious microbes. Viruses
that are not cleared by our immune systems, are common in healthy people, and can
complicate transplantation include cytomegalovirus (CMV) and Torque
teno virus (TTV), which was first described in 1997 [<a href="http://www.ncbi.nlm.nih.gov/pubmed/11148004">review</a>]. TTV
is a small (3.8 kb), single-stranded, transfusion transmitted DNA virus,
representative of a highly diverse family of <a href="http://www.ncbi.nlm.nih.gov/Taxonomy/Browser/wwwtax.cgi?mode=Undef&id=687329&lvl=3&keep=1&srchmode=1&unlock">anelloviruses</a>. <span style="font-family: inherit;"><span style="font-size: small;"> </span></span><br />
<br />
<span style="font-family: inherit;"><span style="font-size: small;">The authors examined the influence of immune-suppressive
drugs (e.g., tacrolimus, mycophenolate mofitil, cyclosporine) and the anti-CMV
drug valgancyclovir on chronic, endogenous microbes. From 96 heart or lung transplant recipients
they collected 656 blood samples over time, some up to a year post-transplant, removed
the cells, and identified remaining DNA by sequencing. They found that 0.12% matched viral or
bacterial or fungal sequences. They
validated some ‘hits’ with quantitative PCR.
Control preparations using water or bacteriophage demonstrated no
relevant artifacts or contamination. </span></span><br />
<div class="MsoNormal">
<br />
<a href="http://3.bp.blogspot.com/-NJv-ncZ7VVs/UqU16iWq06I/AAAAAAAABRc/slAfJytFYYk/s1600/F5A.jpg" imageanchor="1" style="clear: left; float: left; margin-bottom: 1em; margin-right: 1em;"><img border="0" src="http://3.bp.blogspot.com/-NJv-ncZ7VVs/UqU16iWq06I/AAAAAAAABRc/slAfJytFYYk/s400/F5A.jpg" height="323" width="400" /></a><span style="font-family: inherit;"><span style="font-size: small;">They found that treatment with valgancyclovir reduced
herpesviruses, including CMV, but dramatically increased the relative and
absolute levels of anelloviruses, including TTVs (fig. 2, 3, 4). Moreover, those <b>patients who did not reject
their transplants tended to have a greater increase in anelloviruses</b> (Fig. 5A,
shown; rejecting patients plotted in red).
The authors conclude that anellovirus levels might be used to monitor
immune competence. Focosi et al. made a <a href="http://www.ncbi.nlm.nih.gov/pubmed/20034850">related observation following autologous stem cell transplantation</a>. </span></span><br />
<br />
<div class="separator" style="clear: both; text-align: center;">
<a href="http://www.ncbi.nlm.nih.gov/pubmed/24267896" imageanchor="1" style="clear: left; float: left; margin-bottom: 1em; margin-right: 1em;"><img alt="" border="0" src="http://3.bp.blogspot.com/-HotsKifYQA0/RbOP1xJJgVI/AAAAAAAABCI/Ps4DLhNq0f0/s1600/pubmed.gif" title="Link to PubMed" /></a></div>
<span style="font-family: inherit;"><span style="font-size: small;"> Cell. 2013 Nov 21;155(5):1178-87. Temporal
response of the human virome to immunosuppression and antiviral therapy. De Vlaminck I, Khush KK, Strehl C, Kohli B, Luikart H, Neff NF, Okamoto J, Snyder TM, Cornfield DN, Nicolls MR, Weill D, BernsteinD, Valantine HA, Quake SR. </span></span></div>
Unknownnoreply@blogger.com0tag:blogger.com,1999:blog-32683882.post-23864753886489472832013-10-27T11:25:00.000-05:002013-10-27T11:37:19.608-05:00Salt develops a taste for Th17 lymphocytes <div class="MsoNormal">
<style>
</style>Helper T lymphocytes that make the hormone interleukin-17 (IL-17),
called Th17 cells, contribute to inflammation and autoimmune diseases (<a href="http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3173690/">review</a>). The development of Th17 cells was known to require IL-23 but
it was not known exactly why.<span style="mso-spacerun: yes;"> </span>To gain
some perspective, the authors measured gene transcripts found in Th17 cells as
they develop over time from naïve mouse T lymphocytes treated with transforming
growth factor-beta (TGFb) and IL-6.<span style="mso-spacerun: yes;"> </span>They
found that <a href="http://www.ncbi.nlm.nih.gov/gene/6446">SGK1</a>, an enzyme that phosphorylates proteins and has been shown
to regulate sodium (Na+) transport and salt (NaCl) balance in other cells, was
induced nearly 200-fold.<span style="mso-spacerun: yes;"> </span>They emphasize
that IL-23 is “critical” to the induction and maintenance of SGK1 but much of that
evidence is relegated to the supplement data.<span style="mso-spacerun: yes;">
</span>“Network analysis” with a computer program strengthened their suspicion
that SGK1 is a “node” in the IL-23 signaling pathway.<span style="mso-spacerun: yes;"> </span><br />
</div>
<div class="MsoNormal">
Mice without SGK1 (SGK1-knockouts, KO) have
fewer Th17 cells that make less IL-17 when treated with IL-23; notably SGK1
deficiency also alters genes regulating other T cell subsets, including interferon-gamma (Ifng),
Tbx21, and Gata3 (see also the previous gloss on transcription factors regulating
Th17).<span style="mso-spacerun: yes;"> </span>To test the role of SGK1, they immunized “floxed” SGK1
(conditional KO) mice with a myelin protein (MOG), which induces in some mouse
strains a multiple sclerosis (MS) like disease called experimental autoimmune
encephalitis (<a href="http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3042885/">EAE</a>).<span style="mso-spacerun: yes;"> </span><b>EAE severity was
significantly reduced in mice without SGK1 in Th17 cells</b> or CD4+ helper T cells, (fig 2a, KO score <1 normal="" vs.="">3), which corresponded with
a greatly reduced number of Th17 cells in the organ targeted by this autoimmune
disease, the central nervous system (CNS).<span style="mso-spacerun: yes;">
</span>They also saw that CNS-infiltrating cells in EAE <i>had</i> expressed IL-17 at one time
(eYFP+, fig 2e) but that expression of IL-17 by CD4 cells was lost in SGK1-KO
animals (eYFP+ IL17-), suggesting that SGK1 was required to maintain
expression. <!--1--><!--1--><!--1--><!--1--></1></div>
<div class="separator" style="clear: both; text-align: center;">
<a href="http://4.bp.blogspot.com/-7u5Y5GqGI_g/Um09rnAZ9CI/AAAAAAAABKI/9suRQpdEn08/s1600/fig5f+IL17+and+IFNg.jpg" imageanchor="1" style="clear: left; float: left; margin-bottom: 1em; margin-right: 1em;"><img border="0" height="193" src="http://4.bp.blogspot.com/-7u5Y5GqGI_g/Um09rnAZ9CI/AAAAAAAABKI/9suRQpdEn08/s400/fig5f+IL17+and+IFNg.jpg" width="400" /></a></div>
That was nice but now the spice – could dietary salt
modulate immunity through SGK1?<span style="mso-spacerun: yes;"> </span><span style="mso-spacerun: yes;"> </span>Indeed, they found that a high salt diet (HSD) accelerates the development of EAE in
normal mice (fig 4e, top 2 lines, trend line offset to the left is HSD) while it does
nothing to the GSK1-KO animals (lower, lines).<span style="mso-spacerun: yes;"> </span>And connecting at least one of the dots between diet and Th17, they found that HSD also increased more than 2-fold Th17 cells and to a lesser degree interferon-gamma expressing cells in
the CNS, and the induction depended on SGK1 (fig 5f, shown, Th17 left, IFNg right; open bars SGK1-CD4-KO).<span style="mso-spacerun: yes;"> </span><span style="mso-spacerun: yes;">A <a href="http://www.ncbi.nlm.nih.gov/pubmed/23467095">companion paper</a> pursued the role of dietary salt in EAE<a href="http://www.ncbi.nlm.nih.gov/pubmed/23467095"> </a> </span><br />
<br />
<a href="http://www.ncbi.nlm.nih.gov/pubmed/23467085" style="clear: left; float: left; margin-bottom: 1em; margin-right: 1em;"><img border="0" src="http://2.bp.blogspot.com/-OZeBwZ-XtcE/Um08cLzrB7I/AAAAAAAABKE/V5i3_iXyGRI/s1600/pubmed.gif" /></a><span style="mso-spacerun: yes;"> </span>Nature. 2013 Apr 25;496(7446):513-7. <span style="mso-spacerun: yes;"> </span><b style="mso-bidi-font-weight: normal;">Induction of pathogenic TH17 cells by
inducible salt-sensing kinase SGK1</b>.<span style="mso-spacerun: yes;">
</span>Wu C, Yosef N, Thalhamer T, Zhu C, Xiao S, Kishi Y, Regev A, Kuchroo VK. Unknownnoreply@blogger.com0tag:blogger.com,1999:blog-32683882.post-51683565154973846382013-04-21T21:48:00.000-05:002013-04-21T21:52:46.914-05:00Recipe for Developing Th17 cells Thymus-dependent “T” lymphocytes develop into several
effector and regulatory lineages, including the well-characterized regulatory
“helper” T (Th) cells that express the cellular differentiation marker 4 (CD4+)
and CD8+ cytotoxic T lymphocytes (CTL, or Tc) that kill virus-infected cells.
The CD4+ Th lineages further differentiate into Th1, Th2, and Treg cells that
help protect against intracellular microbes, or helminthes, or specifically
regulate immune responses, as well as <a href="http://en.wikipedia.org/wiki/T_helper_17_cell">Th17</a> cells, so-called because they make the interleukin-17 (IL17) that
is required for protecting the mucosa against infection by bacteria and
fungi.<span style="mso-spacerun: yes;"> </span><br />
<div class="MsoNormal">
Development of cell lineages is controlled externally by cytokines
and internally by “master” transcription factors.<span style="mso-spacerun: yes;"> </span>RORgt (<a href="http://en.wikipedia.org/wiki/Retinoic-acid-receptor-related_orphan_receptor">retinoic-acid-receptor-related
orphan receptors</a> gamma t) is expressed by Th17 cells and forced expression
of RORgt gene in naïve CD4+ T cells (Th0) makes them express some genes
characteristic of Th17 cells such as the IL-23 receptor and the chemokine
receptor CCR5 but not the full range of Th17 products, which requires other TFs
including STAT3, IRF4, BATF, and I<span style="mso-bidi-font-weight: bold;">kappa</span>B<span style="mso-bidi-font-weight: bold;">zeta</span>.<span style="mso-spacerun: yes;">
</span>Other TFs may replace these for inducing some Th17 genes.<span style="mso-spacerun: yes;"> </span>The myriad of TFs required for more or less
full Th17 function led these investigators to try to sort out how they work
together.<span style="mso-spacerun: yes;"> </span></div>
<div class="MsoNormal">
The authors first looked where these implicated TFs bind on
the genome of Th0 cells treated with Th17-inducing cytokines using chromosome
immune-precipitation (ChIP).<span style="mso-spacerun: yes;"> </span>They then
compared genes that are transcribed, measured using RNA seq, in the absence of
specific TFs, reduced using siRNA, to “build a network model for Th17 cells”. <span style="mso-spacerun: yes;"> </span></div>
<div class="separator" style="clear: both; text-align: center;">
<a href="http://1.bp.blogspot.com/-9sowRkbsz3Y/UXSjQDw-BXI/AAAAAAAABAg/YrDxDhXXjyM/s1600/Fig5D.jpg" imageanchor="1" style="clear: left; float: left; margin-bottom: 1em; margin-right: 1em;"><img border="0" height="640" src="http://1.bp.blogspot.com/-9sowRkbsz3Y/UXSjQDw-BXI/AAAAAAAABAg/YrDxDhXXjyM/s640/Fig5D.jpg" width="408" /></a></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
They propose that TFs BATF and IRF4 bind cooperatively and
open chromosomes to STAT3, which drives transcription of many genes including
the lineage-specifying TF RORgt.<span style="mso-spacerun: yes;"> </span>They
also identify several putative new Th17 regulators, including the AP-1 family
member Fosl2, which they belive is a key TF for Th17 development. <span style="mso-spacerun: yes;"> </span>They derive many complicated, colorful figures.
<span style="mso-spacerun: yes;">A</span> largely understandable, intriguing single figure is 5D, copied
here, which shows that a block of Th17-related genes is increased (red) or decreased
(blue) “log2 fold” (NB the genes, named on the right, are NOT the same) in Th17
cells but not other T cell subsets (Th1, Th2) treated with siRNA suppressing
<a href="http://en.wikipedia.org/wiki/SATB1">Satb1</a> (a “chromatin organizer"), Bcl11b (a zinc finger TF), Jmjd3 (a histone demethylase),
and the old familiar RorC (encoding RORg).<span style="mso-spacerun: yes;"> </span><span style="mso-spacerun: yes;">But why no siRNA for </span><span style="mso-spacerun: yes;">Fosl2? </span></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<br /></div>
<div class="separator" style="clear: both; text-align: center;">
<a href="http://www.ncbi.nlm.nih.gov/pubmed/23021777?dopt=Abstract" imageanchor="1" style="clear: left; float: left; margin-bottom: 1em; margin-right: 1em;"><img border="0" src="http://2.bp.blogspot.com/-uH59T50_mlk/UXSjvzN5tVI/AAAAAAAABAo/bzrU92BiXtQ/s1600/pubmed.gif" /></a></div>
<div class="MsoNormal">
A validated regulatory network for th17 cell
specification.<span style="mso-spacerun: yes;"> </span>Ciofani M, Madar A, Galan
C, Sellars M, Mace K, Pauli F, Agarwal A, Huang W, Parkurst CN, Muratet M,
Newberry KM, Meadows S, Greenfield A, Yang Y, Jain P, Kirigin FK, Birchmeier C,
Wagner EF, Murphy KM, Myers RM, Bonneau R, Littman DR. <span style="mso-spacerun: yes;"> </span>Cell. 2012 Oct 12;151(2):289-303. </div>
Unknownnoreply@blogger.com0tag:blogger.com,1999:blog-32683882.post-4799322899821909592012-12-09T19:19:00.001-05:002012-12-09T19:25:59.352-05:00The peptide binding site accounts for the MHC link to Rheumatoid Arthritis That genes within the major histocompatibility complex (MHC, human HLA) influence
susceptibility to rheumatoid arthritis (RA) has been known for over 40 years, even before HLA nomenclature was well established (e.g., <a href="http://www.ncbi.nlm.nih.gov/pubmed/1138436">Dick et al. 1975</a>). However, the few “classical” HLA genes constitute only a small fraction of the hundreds genes within the <a href="http://www.ncbi.nlm.nih.gov/books/NBK27156/#A576">MHC</a>, which include the inflammatory cytokine tumor necrosis factor (TNF), a key player in RA. Which genes are responsible for the association?<br />
<br />
The authors investigated 5,018 “cases” of RA, all with antibodies against cyclic citrullinated peptides, CCP (i.e, seropositive, accounting for 70% of RA patients [<a href="http://www.ncbi.nlm.nih.gov/pubmed/21647203">review</a>]) and 14,974 health, ethnically matched controls.<br />
<br />
First they tested their ability to “impute” HLA alleles from their SNP data using a
reference panel of 2,767 individuals. Conclusion, not bad: 98% accuracy for “two digit” mapping and >80% for 4 digit (allele). Then they found the most significant nucleotide (p<10^-526!) is part of a codon for amino acid 11 of the HLA-DR beta 1,
and thus not part of the “shared epitope” (a 5-amino acid sequence and antibody epitope linked to RA [<a href="http://www.ncbi.nlm.nih.gov/pubmed/21420962">review</a>]). A valine at this position confers a 3.8-fold higher risk whereas a (polar) serine is protective (the converse of risk). Comparing cases and controls shows a clear difference (shown here, from fig 3). Adding amino acids at positions 71 and 74 improved significance slightly, and alleles with these amino acids were independently shown to confer risk.<br />
<div class="separator" style="clear: both; text-align: center;">
<a href="http://1.bp.blogspot.com/-tZSBawrcFz0/UMUo2hxa4LI/AAAAAAAABAM/Iu_q9PywXoY/s1600/Ray+fig3.jpg" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" height="283" src="http://1.bp.blogspot.com/-tZSBawrcFz0/UMUo2hxa4LI/AAAAAAAABAM/Iu_q9PywXoY/s640/Ray+fig3.jpg" width="640" /></a></div>
<br />
The authors conclude “These results are consistent with a disease model in which
classical HLA genes and proteins are the dominant factors in rheumatoid arthritis pathogenesis, with only a minor contribution from non-HLA loci in the MHC”. It seems that someone might also explore whether these variants bind CCP better!<br />
<br />
<a href="http://www.ncbi.nlm.nih.gov/pubmed/22286218"><img border="0" src="http://3.bp.blogspot.com/-bAiLBm-vTm8/UMUopjBci9I/AAAAAAAABAE/VGCqGZpPWbU/s1600/pubmed.gif" /></a> Raychaudhuri S, Sandor C, Stahl EA, Freudenberg J, Lee HS, Jia X, Alfredsson L, Padyukov L, Klareskog L, Worthington J, Siminovitch KA, Bae SC, Plenge RM, Gregersen PK, de Bakker PI. “Five amino acids in three HLA proteins explain most of the association between MHC and seropositive rheumatoid arthritis.” Nat Genet. 2012 Jan 29;44(3):291-6 Unknownnoreply@blogger.com1tag:blogger.com,1999:blog-32683882.post-15671259779680964312012-10-07T22:28:00.001-05:002012-10-07T22:31:56.573-05:00ENCODE salvages “junk” DNA <span style="font-size: small;">The “ENCyclopedia Of DNA Elements”, <a href="http://www.genome.gov/10005107">ENCODE</a>, founded in 2003 with grants from the NIH Genome Institute, seeks to identify
all the functional parts of the human genome, assessed by DNA and histone
modifications, chromatin looping, transcription factor binding, chromatin
compaction (DNAse accessibility), and transcripts. The <a href="http://www.genome.gov/12513391">collaboration of ~37 groups</a>, first developed technology. Recently they published their
first salvo of <a href="http://www.nature.com/nature/journal/v489/n7414/full/489045a.html?WT.ec_id=NATURE-20120906">30 research papers</a>, several published in Nature along with a <a href="http://www.nature.com/encode/">News & Views</a>. </span> <br />
<div class="MsoNormal">
<span style="font-size: small;">The paper by Djebali and scores of colleagues offers “a
genome-wide catalogue of human transcripts”, together with their location (nucleus
or cytoplasm), and whether they have a 7mG cap 5’ or a poly-A tail 3’. They prepared RNA from 15 human cells lines
after fractionation (whole cell, nucleus and cytosol) and separation of RNA
into short and long (>200 nucleotides).
Long RNAs were further separated into +/- polyA tails. They <a href="http://www.blogger.com/RNAseq%20http://en.wikipedia.org/wiki/RNA-Seq">sequenced</a> these RNAs and determined their initiation sites and their 5’ and 3’ termini (using
technologies felicitously named CAGE and PET). Then they did bioinformatics: compared to annotated
genome (<a href="http://www.gencodegenes.org/">GENCODE</a>) statistics, etc., All these data are
available for your perusal using the <a href="http://genome.crg.cat/encode_RNA_dashboard/">RNA Dashboard</a>.
</span></div>
<div class="MsoNormal">
<span style="font-size: small;">They made many interesting observations; e.g., they conclude
there is very little “junk” DNA. Nearly
75% of the genome is transcribed in at least one of the cell lines, though only
a little over 50% in any given line.
(This is similar to previous findings, albeit not as
“encyclopedic”). Only 28% of the 7,053
small RNAs (including snRNAs, snoRNAs, miRNAs, and tRNAs) annotated by GENCODE
are found in any of these cell lines, suggesting the expression of many
annotated small RNAs is cell type specific. </span></div>
<div class="separator" style="clear: both; text-align: center;">
<a href="http://3.bp.blogspot.com/-vzpi4lFRfY8/UHJFd_zvWFI/AAAAAAAAA_s/93qqDUZYXlo/s1600/F3-encode.jpg" imageanchor="1" style="clear: left; float: left; margin-bottom: 1em; margin-right: 1em;"><img border="0" height="291" src="http://3.bp.blogspot.com/-vzpi4lFRfY8/UHJFd_zvWFI/AAAAAAAAA_s/93qqDUZYXlo/s400/F3-encode.jpg" width="400" /></a></div>
<div class="MsoNormal">
<span style="font-size: small;">They also find that protein-coding transcripts are more
abundant than long non-coding RNAs (lncRNAs) and that the same genes are transcribed
in different cells. Figure 3, shown
here, plots the number of transcripts (r.p.k.m., reads per kilobase per million
reads) on the x axis vs. the ratio of nuclear/cytoplasmic for protein-coding
(orange), which are abundant (right) in the cytoplasm (down), non-coding (blue), and novel intergenic (green),
which tend to be expressed at lower levels (left) and mostly nuclear (up). A few individual transcripts are also
identified, giving appreciation for the range of expression. </span></div>
<div class="MsoNormal">
<span style="font-size: small;">Also not for the first time, they suggest that shrinking “intergenic”
regions <span style="font-family: AdvOT1ef757c0;">“prompts the
reconsideration of the definition of a gene”. </span> They<span style="font-family: AdvOT1ef757c0;"> “propose that the transcript
be considered as the basic atomic unit of inheritance”</span>
and that “<span style="font-family: AdvOT1ef757c0;">gene … denote … all those transcripts …. that contribute to a
given phenotypic trait". Mendel would
approve. </span></span><br />
<div class="cit">
<a href="http://www.ncbi.nlm.nih.gov/pubmed/22955620" imageanchor="1" style="clear: left; float: left; margin-bottom: 1em; margin-right: 1em;"><img border="0" src="http://1.bp.blogspot.com/-XizhOXImYRc/UHJHiL7ZEnI/AAAAAAAAA_0/12jU_-1Dc5o/s1600/pubmed.gif" /></a><a href="http://www.ncbi.nlm.nih.gov/pubmed/22955620#" role="button" title="PubMed.">PubMed.</a> Djebali et al.<span style="font-weight: normal;"><span style="font-size: small;"> "Landscape of transcription in human cells." </span></span>2012 Nature Sep 6;489(7414):101-8. </div>
</div>
Unknownnoreply@blogger.com0