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All, Here is an interesting new study  (popular press story) that I appreciated as much for its data as its conclusions. In it, researchers identified a group of ~1400 "Wellderly" individuals - which they defined as: ndividuals who are >80 years old with no chronic diseases and who are not taking chronic medications. As you might imagine, these folks are pretty rare, and so they wanted to compare their genomes with those of an average population of elderly people. But first, they did an interesting thing - they compared the longevity of the siblings of the Wellderly cohort (who share a lot of genetics, and probably some lifestyle factors too, with the Wellderly folks) to see how their lifespan compares with the average US population. Here are the "survival curves" for the Wellderly siblings (red) vs. average folks (blue): As you can see, the Wellderly siblings had a more square mortality curve, but their survival curve wasn't shifted right - i.e. their "maximum lifespan" wasn't any longer than the average folks. Instead, both curves hit (near) zero around 100 years. Like the Wellderly themselves, their siblings appear to avoid / postpone the diseases of aging, and so do better in the "middle years" of elderliness (65-85), but beyond that have a mortality rate similar to the population as a whole. They then looked at the Wellderly folks' genetics. Interestingly, they didn't find their genomes to be particularly enriched with so-called "longevity genes" - those that have been identified as more common in centenarians or other very long-lived people. In other words, these folks are healthy agers, but don't seem to be blessed with genes for extreme longevity, which I thought was interesting. It suggests that at least to some degree healthy aging and extreme longevity are distinct, based both on the (sibling) survival curve data and their own genetics. Here is how the authors summarized this part of their findings: [O]ur results suggest that healthy aging is a genetically overlapping but divergent phenotype from exceptional longevity and that the healthy aging phenotype is potentially enriched for heritable components of both reduced risk of age-associated disease and resistance to age-associated disease. I'm curious what Michael would say, but it seems like this apparent distinction between disease avoidance and extreme longevity might undermine to some degree the SENS hypothesis - that aging simple is the accumulation of damage from the diseases of aging. Note: that is my potentially inaccurate summary of the SENS hypothesis... But what I found personally most interesting and helpful from this paper were two of their tables, listing the various genetic markers they tested for both longevity and Alzheimer's disease (AD). They quite explicitly listed the SNPs and which alleles of those SNPs are associated with longevity or AD. I've reproduced the two tables below, and added my own data, a friend's 23andMe data I have access to, and links to 23andMe so that any other 23andMe customers can check their own status for the corresponding SNPs. I've even added a tally at the bottom of each table with a genetic "score" - basically the number of "good" alleles one carries minus (in the case of the AD table) the number of "bad" alleles one carries. Although in the case of AD, it was the evil APOE4 allele that dominated - i.e. the biggest difference between the genes of the "Wellderly" folks and the average population was that the Wellderly were a lot less likely to carry APOE4 alleles. Anyway, here are the tables. First, the table with the SNPs and alleles previously identified (via other studies) to be associated with increased longevity. The "Longevity Allele" column shows that variant of the SNP that has been shown to be associated with increased longevity. The second column shows the gene the SNP is part of - as you can see many familiar names, including FOXO3, SIRT1, IL-6, IGF1, AKT (all of which I note have been associated with both CR and Cold Exposure in one way or another). The green letters show when I or "Person X" are carriers for the "good" longevity allele: Here are "live" links to the 23andMe page for each SNP so 23andMe customers can check their own results on these SNPs: https://www.23andme.com/you/explorer/snp/?snp_name=rs2802292 https://www.23andme.com/you/explorer/snp/?snp_name=rs1935949 https://www.23andme.com/you/explorer/snp/?snp_name=rs3758391 https://www.23andme.com/you/explorer/snp/?snp_name=rs5882 https://www.23andme.com/you/explorer/snp/?snp_name=rs1042522 https://www.23andme.com/you/explorer/snp/?snp_name=rs1800795 https://www.23andme.com/you/explorer/snp/?snp_name=rs2811712 https://www.23andme.com/you/explorer/snp/?snp_name=rs34516635 https://www.23andme.com/you/explorer/snp/?snp_name=rs2542052 https://www.23andme.com/you/explorer/snp/?snp_name=rs3803304 Here is the same sort of table, but this time for SNPs and Alleles associated with Alzheimer's disease and/or cognitive decline. Note, the last SNP in the table is the dreaded APOE4. As you can see from the p-value column, the APOE4 allele was far and away the most significant predictor of AD/cognitive decline, and the Wellderly had it less frequently that the general population (the column labelled "ITMI A2 Freq"). Also not that unlike the longevity SNPs, 23andMe didn't have data for many of the AD-related SNPs. Once again, the green letters show when I or "Person X" are carriers for the "good" allele (for avoiding AD) or and red letters show where one of us is a carrier for the "bad" allele (increasing risk of AD): Here are the direct links to 23andMe for the subset of SNPs from the table that were available (at least for me): https://www.23andme.com/you/explorer/snp/?snp_name=rs190982 https://www.23andme.com/you/explorer/snp/?snp_name=rs2718058 https://www.23andme.com/you/explorer/snp/?snp_name=rs1476679 https://www.23andme.com/you/explorer/snp/?snp_name=rs11771145 https://www.23andme.com/you/explorer/snp/?snp_name=rs11218343 https://www.23andme.com/you/explorer/snp/?snp_name=rs17125944 https://www.23andme.com/you/explorer/snp/?snp_name=rs10498633 https://www.23andme.com/you/explorer/snp/?snp_name=rs2075650 As you can see, for both the longevity SNPs and the AD SNPs, my score is a bit better than the score for my friend, "Person X" - so I got that goin' for me. And they are an unfortunate carrier of one APOE4 allele. ☹ To wrap up, the researchers also also found that a few of the Wellderly folks were enriched with an ultra-rare variants of a gene that seems to be especially protective against AD, called COL25A1 but I couldn't figure out what SNPs or alleles they were talking about. As always, these genetic marker studies need to be taken with a grain of salt. But it was fun to see where I and "Person X" stand regarding all these variants. I'd be curious if anyone else would be willing to share their data, or at least their "scores". --Dean -------  Cell (2016), http://dx.doi.org/10.1016/j.cell.2016.03.022 Whole-Genome Sequencing of a Healthy Aging Cohort Galina A. Erikson5, Dale L. Bodian5, Manuel Rueda, Bhuvan Molparia, Erick R. Scott, Ashley A. Scott-Van Zeeland, Sarah E. Topol, Nathan E. Wineinger, John E. Niederhuber, Eric J. Topol6, Ali Torkamani6 Free full text: http://www.cell.com/cell/pdf/S0092-8674(16)30278-1.pdf Summary Studies of long-lived individuals have revealed few genetic mechanisms for protection against age-associated disease. Therefore, we pursued genome sequencing of a related phenotype—healthy aging—to understand the genetics of disease-free aging without medical intervention. In contrast with studies of exceptional longevity, usually focused on centenarians, healthy aging is not associated with known longevity variants, but is associated with reduced genetic susceptibility to Alzheimer and coronary artery disease. Additionally, healthy aging is not associated with a decreased rate of rare pathogenic variants, potentially indicating the presence of disease-resistance factors. In keeping with this possibility, we identify suggestive common and rare variant genetic associations implying that protection against cognitive decline is a genetic component of healthy aging. These findings, based on a relatively small cohort, require independent replication. Overall, our results suggest healthy aging is an overlapping but distinct phenotype from exceptional longevity that may be enriched with disease-protective genetic factors. PMID: Unavailable
There is an new study on the link between genetics and obesity reported on in this popular press article: http://www.huffingtonpost.com/entry/obesity-gene-discovery-could-forever-change-weight-loss_55d4f994e4b0ab468d9fc0f4 Study  is the (rather technical) abstract for the paper associated with the story. I'll do my best to summarize the background and the findings of this study, which I found really interesting. First a little background. It has been known for a while that a particular gene on chromosome 16 named FTO has many (over 200) SNPs (single nucleotide polymorphisms - i.e. common variations in particular base pairs along this gene), several of which appear to be associated with obesity. Here are two older studies  that address this linkage. Study  focused on SNP rs9939609. It found that people who carry one (or especially two) copies of the 'obese' allele ('A') for this SNP were significantly more likely to be obese than those who carry the 'lean' variant ('T'). Study  found the same thing for three other FTO SNPs, rs1421085, rs17817449 and rs8043757. It found that people with the 'obese' variants for these three SNPs ('C', 'G' and 'T', respectively) were about 2.5 times more likely to be obese than those who had the lean variants for these three SNPs ('T', 'T', 'A', respectively). The newest study , focused on the first of the three SNPs from , namely SNP rs1421085, and did something really cool and cutting edge. They took fat cells from mice and humans and used the recently-developed CRISPR gene editing technique to change this particular SNP from the 'obese' variant ('C') to the 'lean' variant ('T'), and then observed what happened to the cells. What they found was that the fat cells converted from being thermogenically active, 'beige' fat cells (i.e. like brown fat cells) to 'white' fat cells that are much more efficient at storing fat, rather than burning it. This can be spun as a nice mechanistic story to explain why at least this SNP is associated with obesity. People who have 'C' for rs1421085 produce more white fat cells, making them more efficient at storing fat - i.e. they have a more 'thrifty' genotype and will therefore (presumably) store more fat for a given calorie intake. Now comes the interesting citizen science part. Data on all four of obesity-related SNPs mentioned above are available to subscribers of 23andMe. Simply log in, then go to this page: https://www.23andme.com/you/explorer/gene/?gene_name=FTO to get a list of all 200+ SNPs from the FTO gene that 23andMe sequences, and search on the page for these four SNPs. Here are my results: rs9939609 TT (lean variant = T) rs1421085 TT (lean variant = T) rs17817449 TT (lean variant = T) rs8043757 AA (lean variant = A) As you can see, I've inherited two copies (one from each of my parents) of the 'lean' allele for each of these four SNPs. So it is no wonder that unintended weight gain has never been an problem for me - at least according to these SNPs I have the antithesis of the 'thrifty genotype'. I'm curious what other CRONies who are also subscribers to 23andMe have for these SNPs, and whether they consider themselves to have a 'thrifty genotype' (easily gain weight) or not. I also wonder whether long-term success on a CR lifestyle is in any way correlated with the values for these SNPs. There is some indication  that some of the FTO SNPs (including rs9939609) have an effect on energy intake and preference for energy dense (i.e. high fat) foods, and from  we saw that people with the 'obese' allele for rs9939609 and who eat a high-fat, low-carb diet have a higher BMI, which could discourage people trying to practice CR in order to lose weight. Conversely, having a 'thrifty genotype' might make it easier to maintain a low calorie intake without becoming terribly skinny, which can sometimes result in social pressure to eat more to avoid looking like a concentration camp victim. :) Anyway, I've probably grossly oversimplified the science, but I found it fascinating and would be interested to hear what other 23andMe subscribers have for these alleles. --Dean -------------------------------  N Engl J Med. 2015 Aug 19. [Epub ahead of print] FTO Obesity Variant Circuitry and Adipocyte Browning in Humans. Claussnitzer M(1), 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 M. Background Genomewide association studies can be used to identify disease-relevant genomic regions, but interpretation of the data is challenging. The FTO region harbors the strongest genetic association with obesity, yet the mechanistic basis of this association remains elusive. Methods We examined epigenomic data, allelic activity, motif conservation, regulator expression, and gene coexpression patterns, with the aim of dissecting the regulatory circuitry and mechanistic basis of the association between the FTO region and obesity. We validated our predictions with the use of directed perturbations in samples from patients and from mice and with endogenous CRISPR-Cas9 genome editing in samples from patients. Results Our data indicate that the FTO allele associated with obesity represses mitochondrial thermogenesis in adipocyte precursor cells in a tissue-autonomous manner. The rs1421085 T-to-C single-nucleotide variant disrupts a conserved motif for the ARID5B repressor, which leads to derepression of a potent preadipocyte enhancer and a doubling of IRX3 and IRX5 expression during early adipocyte differentiation. This results in a cell-autonomous developmental shift from energy-dissipating beige (brite) adipocytes to energy-storing white adipocytes, with a reduction in mitochondrial thermogenesis by a factor of 5, as well as an increase in lipid storage. Inhibition of Irx3 in adipose tissue in mice reduced body weight and increased energy dissipation without a change in physical activity or appetite. Knockdown of IRX3 or IRX5 in primary adipocytes from participants with the risk allele restored thermogenesis, increasing it by a factor of 7, and overexpression of these genes had the opposite effect in adipocytes from nonrisk-allele carriers. Repair of the ARID5B motif by CRISPR-Cas9 editing of rs1421085 in primary adipocytes from a patient with the risk allele restored IRX3 and IRX5 repression, activated browning expression programs, and restored thermogenesis, increasing it by a factor of 7. Conclusions Our results point to a pathway for adipocyte thermogenesis regulation involving ARID5B, rs1421085, IRX3, and IRX5, which, when manipulated, had pronounced pro-obesity and anti-obesity effects. (Funded by the German Research Center for Environmental Health and others.). PMID: 26287746 ---------------  Br J Nutr. 2012 Nov 28;108(10):1859-65. doi: 10.1017/S0007114511007410. Epub 2012 Jan 23. Association of the fat mass and obesity-associated (FTO) gene variant (rs9939609) with dietary intake in the Finnish Diabetes Prevention Study. Lappalainen T(1), Lindström J, Paananen J, Eriksson JG, Karhunen L, Tuomilehto J, Uusitupa M. A cluster of variants in the fat mass and obesity-associated (FTO) gene are associated with the common form of obesity. Well-documented dietary data are required for identifying how the genetic risk can be modified by dietary factors. The objective of the present study was to investigate the associations between the FTO risk allele (rs9939609) and dietary intake, and to evaluate how dietary intake affects the association between FTO and BMI in the Finnish Diabetes Prevention Study during a mean follow-up of 3·2 years. A total of 479 (BMI >25 kg/m2) men and women were genotyped for rs9939609. The participants completed a 3 d food record at baseline and before every annual study visit. The average intakes at baseline and during the years 1, 2 and 3 were calculated. At baseline, the FTO variant rs9939609 was not associated with the mean values of total energy intake, macronutrients or fibre. At baseline, a higher BMI by the FTO risk genotype was detected especially in those who reported a diet high in fat with mean BMI of 30·6 (sd 4·1), 31·3 (sd 4·6) and 34·5 (sd 6·2) kg/m2 for TT, TA and AA carriers, respectively (P =0·005). Higher BMI was also observed in those who had a diet low in carbohydrates (P =0·028) and fibre (P =0·015). However, in the analyses adjusted for total energy intake, age and sex, significant interactions between FTO and dietary intakes were not found. These findings suggest that the association between the FTO genotype and obesity is influenced by the components of dietary intake, and the current dietary recommendations are particularly beneficial for those who are genetically susceptible for obesity. PMID: 22265018 -----------------------  Gene. 2015 Mar 1;558(1):75-81. doi: 10.1016/j.gene.2014.12.050. Epub 2014 Dec 24. Common variations in the FTO gene and obesity in Thais: a family-based study. Chuenta W(1), Phonrat B(2), Tungtrongchitr A(3), Limwongse C(4), Chongviriyaphan N(5), Santiprabhob J(6), Tungtrongchitr R(7). Several studies have revealed the association between single nucleotide polymorphisms (SNPs) in the first intron of fat mass and obesity-associated (FTO) gene and obesity. To date, more than 100 SNPs in the FTO gene have been identified in various populations. Nevertheless, this association has not yet been confirmed in Thai populations. The aim of this study was to investigate whether FTO variants are associated with obesity in Thais. We analyzed ten variants in the FTO gene (rs9939609, rs9926289, rs8050136, rs9930501, rs9930506, rs9940646, rs9940128, rs1421085, rs17817449, and rs8043757) in 12 families (83 persons); composed of 12 proband cases and 71 associated family members. All participants were genotyped using polymerase chain reaction (PCR) method and DNA sequencing assay. We found significant associations between three SNPs located in the first intron of FTO gene (rs1421085, rs17817449, and rs8043757) and obesity. The odds ratios were 2.82 (95% CI, 1.16-6.90, p=0.02) for rs1421085 and rs17817449, and 3.15 (95% CI, 1.28-7.76, p=0.01) for rs8043757. Strong linkage disequilibrium among ten SNPs was observed (D'>0.8). Haplotype analysis (combination of rs1421085 (T/C), rs17817449 (T/G), and rs8043757 (A/T)) showed that the CGT haplotype is associated with an increased risk of obesity (OR, 2.42; 95% CI, 1.18-4.97; p=0.018) when compared to the reference haplotype (TTA). The SNPs rs1421085, rs17817449 and rs8043757 in the first intron of the FTO gene are associated with increasing risk of obesity in Thais. Copyright © 2014 Elsevier B.V. All rights reserved. PMID: 25542809 [PubMed - indexed for MEDLINE] ------------------  N Engl J Med. 2008 Dec 11;359(24):2558-66. doi: 10.1056/NEJMoa0803839. An obesity-associated FTO gene variant and increased energy intake in children. Cecil JE(1), Tavendale R, Watt P, Hetherington MM, Palmer CN. Author information: (1)Bute Medical School, University of St Andrews, St Andrews, United Kingdom. Comment in N Engl J Med. 2009 Apr 9;360(15):1571-2; author reply 1572. N Engl J Med. 2008 Dec 11;359(24):2603-4. BACKGROUND: Variation in the fat mass and obesity-associated (FTO) gene has provided the most robust associations with common obesity to date. However, the role of FTO variants in modulating specific components of energy balance is unknown. METHODS: We studied 2726 Scottish children, 4 to 10 years of age, who underwent genotyping for FTO variant rs9939609 and were measured for height and weight. A subsample of 97 children was examined for possible association of the FTO variant with adiposity, energy expenditure, and food intake. RESULTS: In the total study group and the subsample, the A allele of rs9939609 was associated with increased weight (P=0.003 and P=0.049, respectively) and body-mass index (P=0.003 and P=0.03, respectively). In the intensively phenotyped subsample, the A allele was also associated with increased fat mass (P=0.01) but not with lean mass. Although total and resting energy expenditures were increased in children with the A allele (P=0.009 and P=0.03, respectively), resting energy expenditure was identical to that predicted for the age and weight of the child, indicating that there is no defect in metabolic adaptation to obesity in persons bearing the risk-associated allele. The A allele was associated with increased energy intake (P=0.006) independently of body weight. In contrast, the weight of food ingested by children who had the allele was similar to that in children who did not have the allele (P=0.82). CONCLUSIONS: The FTO variant that confers a predisposition to obesity does not appear to be involved in the regulation of energy expenditure but may have a role in the control of food intake and food choice, suggesting a link to a hyperphagic phenotype or a preference for energy-dense foods. 2008 Massachusetts Medical Society PMID: 19073975