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A genome-wide association approach to study 1507 children from the Avon Longitudinal Study of Parents and Children (ALSPAC) was applied to identify genetic determinants underlying variation in 2D:4D. The results demonstrated that a variant within the LIN28B gene is associated with 2D:4D and is significant for the early development of the hands and is also associated with height and age at menarche.

A study uses a novel method called functional gene group analysis to test the effect of groups of genes, which are defined according to their cellular function, on cognitive ability. The analysis reveals that synaptic heterotrimeric guanine nucleotide binding proteins (G proteins) play a key role in cognitive ability, thereby offering fresh insights into the genetic basis of cognitive ability.

The adipocyte-derived protein adiponectin is highly heritable and inversely associated with risk of type 2 diabetes mellitus (T2D) and coronary heart disease (CHD). We meta-analyzed 3 genome-wide association studies for circulating adiponectin levels (n = 8,531) and sought validation of the lead single nucleotide polymorphisms (SNPs) in 5 additional cohorts (n = 6,202). Five SNPs were genome-wide significant in their relationship with adiponectin (P≤5×10−8). We then tested whether these 5 SNPs were associated with risk of T2D and CHD using a Bonferroni-corrected threshold of P≤0.011 to declare statistical significance for these disease associations. SNPs at the adiponectin-encoding ADIPOQ locus demonstrated the strongest associations with adiponectin levels (P-combined = 9.2×10−19 for lead SNP, rs266717, n = 14,733). A novel variant in the ARL15 (ADP-ribosylation factor-like 15) gene was associated with lower circulating levels of adiponectin (rs4311394-G, P-combined = 2.9×10−8, n = 14,733). This same risk allele at ARL15 was also associated with a higher risk of CHD (odds ratio [OR] = 1.12, P = 8.5×10−6, n = 22,421) more nominally, an increased risk of T2D (OR = 1.11, P = 3.2×10−3, n = 10,128), and several metabolic traits. Expression studies in humans indicated that ARL15 is well-expressed in skeletal muscle. These findings identify a novel protein, ARL15, which influences circulating adiponectin levels and may impact upon CHD risk.

To identify genetic variants associated with birth weight, we meta-analyzed six genome-wide association (GWA) studies (n = 10,623 Europeans from pregnancy/birth cohorts) and followed up two lead signals in 13 replication studies (n = 27,591). rs900400 near LEKR1 and CCNL1 (P = 2 x 10(-35)) and rs9883204 in ADCY5 (P = 7 x 10(-15)) were robustly associated with birth weight. Correlated SNPs in ADCY5 were recently implicated in regulation of glucose levels and susceptibility to type 2 diabetes, providing evidence that the well-described association between lower birth weight and subsequent type 2 diabetes has a genetic component, distinct from the proposed role of programming by maternal nutrition. Using data from both SNPs, we found that the 9% of Europeans carrying four birth weight-lowering alleles were, on average, 113 g (95% CI 89-137 g) lighter at birth than the 24% with zero or one alleles (P(trend) = 7 x 10(-30)). The impact on birth weight is similar to that of a mother smoking 4-5 cigarettes per day in the third trimester of pregnancy.

Tooth development is a highly heritable process which relates to other growth and developmental processes, and which interacts with the development of the entire craniofacial complex. Abnormalities of tooth development are common, with tooth agenesis being the most common developmental anomaly in humans. We performed a genome-wide association study of time to first tooth eruption and number of teeth at one year in 4,564 individuals from the 1966 Northern Finland Birth Cohort (NFBC1966) and 1,518 individuals from the Avon Longitudinal Study of Parents and Children (ALSPAC). We identified 5 loci at P<5x10(-8), and 5 with suggestive association (P<5x10(-6)). The loci included several genes with links to tooth and other organ development (KCNJ2, EDA, HOXB2, RAD51L1, IGF2BP1, HMGA2, MSRB3). Genes at four of the identified loci are implicated in the development of cancer. A variant within the HOXB gene cluster associated with occlusion defects requiring orthodontic treatment by age 31 years., Competing Interests: The authors have declared that no competing interests exist.

The adipocyte-derived protein adiponectin is highly heritable and inversely associated with risk of type 2 diabetes mellitus (T2D) and coronary heart disease (CHD). We meta-analyzed 3 genome-wide association studies for circulating adiponectin levels (n = 8,531) and sought validation of the lead single nucleotide polymorphisms (SNPs) in 5 additional cohorts (n = 6,202). Five SNPs were genome-wide significant in their relationship with adiponectin (P< or =5x10(-8)). We then tested whether these 5 SNPs were associated with risk of T2D and CHD using a Bonferroni-corrected threshold of P< or =0.011 to declare statistical significance for these disease associations. SNPs at the adiponectin-encoding ADIPOQ locus demonstrated the strongest associations with adiponectin levels (P-combined = 9.2x10(-19) for lead SNP, rs266717, n = 14,733). A novel variant in the ARL15 (ADP-ribosylation factor-like 15) gene was associated with lower circulating levels of adiponectin (rs4311394-G, P-combined = 2.9x10(-8), n = 14,733). This same risk allele at ARL15 was also associated with a higher risk of CHD (odds ratio [OR] = 1.12, P = 8.5x10(-6), n = 22,421) more nominally, an increased risk of T2D (OR = 1.11, P = 3.2x10(-3), n = 10,128), and several metabolic traits. Expression studies in humans indicated that ARL15 is well-expressed in skeletal muscle. These findings identify a novel protein, ARL15, which influences circulating adiponectin levels and may impact upon CHD risk., Competing Interests: The authors have declared that no competing interests exist.

Genome-wide association studies using thousands to hundreds of thousands of single nucleotide polymorphism (SNP) markers and region-wide association studies using a dense panel of SNPs are already in use to identify disease susceptibility genes and to predict disease risk in individuals. Because these tasks become increasingly important, three different data sets were provided for the Genetic Analysis Workshop 15, thus allowing examination of various novel and existing data mining methods for both classification and identification of disease susceptibility genes, gene by gene or gene by environment interaction. The approach most often applied in this presentation group was random forests because of its simplicity, elegance, and robustness. It was used for prediction and for screening for interesting SNPs in a first step. The logistic tree with unbiased selection approach appeared to be an interesting alternative to efficiently select interesting SNPs. Machine learning, specifically ensemble methods, might be useful as pre-screening tools for large-scale association studies because they can be less prone to overfitting, can be less computer processor time intensive, can easily include pair-wise and higher-order interactions compared with standard statistical approaches and can also have a high capability for classification. However, improved implementations that are able to deal with hundreds of thousands of SNPs at a time are required.