Aging-related Traits and Disease Risk Factors in a Sardinian Population Cohort

撒丁岛研究人群队列包括来自撒丁岛四个城镇集群的7000多名受试者，年龄从14岁到102岁不等。这项研究一直在测量可连续评分的300个数量性状(内表型或量化风险相关遗传或环境因素)，并被设计为纵向研究，在其任期的前13年中有4次访问。特别令人感兴趣的特征包括一系列心血管风险因素、人体测量、血液测试值和个性方面。目前正在为研究队列进行第四次访问，以评估纵向趋势和结果，以及评估与年龄相关的骨密度和脆弱程度的其他表型。例如，24小时血压测量和超声心动图正在扩大对心血管特征的分析；队列正在专门扩大到超过250名92岁以上的人，以分析极端年龄的影响。 在这个队列中，进行了带有单核苷酸标记电池的全基因组扫描，并在去年补充了全基因组DNA测序和使用专门芯片(代谢物芯片、免疫芯片和外显子芯片，以及一个旨在对整个基因组提供同等覆盖的芯片)的基因分型。这些研究提供了一个超过17,000,000个变种的目录，其中包括一系列相对罕见的变种，这些变种正在基因组范围的关联扫描中测试与特征和疾病的关联。此外，1000人提供了淋巴细胞样本以供分析(见下文)。 在到目前为止的研究中，GWAS指出了基因/变种，这些基因/变种决定了所研究的每种性状和疾病的很大一部分遗传变异。随着财团在其他人群队列上的努力，包括巴尔的摩老龄化纵向研究和NIA支持的Inchianti研究，越来越多的出版物确定了与肥胖、心血管特征以及血脂和血液成分水平有关的基因。特别是，与HbF水平有关的基因被确定为地中海贫血/镰状细胞疾病严重程度的调节因素，以及决定血压的遗传因素的发现，许多基因决定肥胖；个性方面影响体重过轻和超重(完整列表见参考文献)。结果的广度和深度得到了3篇最新论文的支持：其中一篇是根据队列中1,204条Y染色体的DNA序列重建的；第二篇推断的DNA变体控制着95种分离的免疫细胞类型中至少一种的高达80%的变异性；第三篇论文确定了一个与部分受教育程度的遗传能力有关的遗传位点。 在过去一年的另一项新举措中，通过流动分选对3400人进行了95种免疫系统细胞的分离，以确定一般白细胞亚群(B和T、自然杀伤细胞、单核细胞等)的水平。T调节细胞、树突状细胞和T细胞成熟阶段的亚类；许多细胞类型的水平变化，特别是Tregs的水平高达87%是由遗传决定的；对具有12,500,000个SNP集的1,200个个体的Gwas分析显示，23个对至少一种细胞类型有较大影响。例如，R262W SH2B3变异体已经与几种自身免疫性疾病和造血负调控相关，被证明特别影响CD4+T细胞的数量，可能导致功能丧失。 在一种互补的方法中，撒丁岛患者和对照组的队列被聚集在一起，并对I型糖尿病、多发性硬化症(MS)和乳腺癌等几种疾病中的每一种进行GWA型基因分型。在3,000多名患者和3,500名对照中发现了大约660万个SNPs，发现CBLB与多发性硬化症有关。从技术上讲，CBLB参与多发性硬化症在撒丁岛更容易找到，但现在已在其他患者队列中广泛复制。 我们的分析扩展了变异与疾病的关联，以指定等位基因对其产生影响的细胞类型。这为可能的最终干预提供了进一步的标记和潜在的分子和细胞靶点。

The SardiNIA study population cohort comprises over 7,000 subjects, starting at ages from 14-102, from a cluster of four towns in Sardinia. The study has been measuring >300 quantitative traits (endophenotypes or quantitative risk-related genetic or environmental factors) that can be scored on a continuous scale, and is designed as a longitudinal studies, with 4 visits over the first 13 years of its tenure. Traits of special interest include a range of cardiovascular risk factors, anthropometric measurements, blood test values, and facets of personality. Fourth visits are now in progress for the study cohort to permit the assessment of longitudinal trends and outcomes, as well as the assessment of additional phenotypes related to bone density and frailty as a function of age. For example, 24 hour blood pressure measurements and ECHOcardiography are extending the analysis of cardiovascular traits; and the cohort is being specifically extended to over 250 individuals over 92 years of age to analyze effects of extreme age. With this cohort, full-genome scans with batteries of single-nucleotide markers were conducted, and were supplemented in the last year with full genome DNA sequencing and genotyping with specialized chips (metabochip, immunochip, and exome chip, and a chip designed to give equal coverage across the entire genome). These have provided a catalogue of over 17,000,000 variants, including a range of relatively rare variants, which are being tested for association with traits and diseases in Genome-wide association scans (GWAS). In addition, 1,000 individuals have provided lymphocyte samples for analysis (see below). In studies thus far, GWAS have pointed to genes/variants that determine a significant portion of the genetic contribution to variance for each trait and disease studied. In conjunction with consortium efforts on other population cohorts, including the Baltimore Longitudinal Study of Aging and the InCHIANTI study supported by the NIA, an increasing number of publications have resulted that identify genes associated with obesity, cardiovascular traits, and levels of lipids and blood components. In particular, genes associated with HbF levels as a modulator of thalassemia/sickle cell disease severity have been identified, as well as findings of genetic factors determining loci for blood pressure, many affecting adiposity; and personality facets affecting under- and over-weight (see bibliography for a complete list). Supporting the range and depth of results are 3 of the most recent publications: in one, human demographic history was reconstructed from DNA sequences of 1,204 Y chromosomes in the cohort; a second inferred DNA variants that control up to 80% of the variability of at least one of 95 separated immune cell types; and a third identified a genetic locus that is associated with part of hereditary capacity for educational attainment. In an additional new initiative in the past year, separation of 95 types of immune system cells was done for 3,400 individuals by flow-sorting to determine levels of general leukocyte sub-populations (B and T, natural killer, monocytes, etc.) and subclasses of T-regulatory cells, dendritic cells, and T cell maturation stages; the variation of levels of many cell types especially Tregs is up to 87% genetically determined; and GWAS analysis on 1,200 individuals with the 12,500,000 SNP set then revealed 23 with a large effect on at least one cell type. For example, the R262W SH2B3 variant, already associated with several autoimmune diseases and negative regulation of hematopoiesis, was shown to particularly affect the numbers of CD4+ T cells, likely resulting in a loss of function. In a complementary approach, cohorts of Sardinian patients and controls were assembled and genotyped for GWAS for each of several diseases, Type 1 diabetes, multiple sclerosis (MS), and breast cancer. GWAS with approximately 6.6 million SNPs in over 3,000 patients and 3,500 controls identified CBLB as associated with MS. CBLB involvement in MS was technically easier to find in Sardinia, but has now been widely replicated in other patient cohorts. Our analyses extend associations of variants with a disease to specify the cell types in which the alleles have their effects. This provides a further step in supplying markers and potential molecular and cellular targets for possible eventual intervention.