Genome-wide association studies have identified hundreds of genetic variants associated with complex human diseases and traits, and have provided valuable insights into their genetic architecture. Most variants identified so far confer relatively small increments in risk, and explain only a small proportion of familial clustering, leading many to question how the remaining, 'missing' heritability can be explained. Here we examine potential sources of missing heritability and propose research strategies, including and extending beyond current genome-wide association approaches, to illuminate the genetics of complex diseases and enhance its potential to enable effective disease prevention or treatment.Many common human diseases and traits are known to cluster in families and are believed to be influenced by several genetic and environmental factors, but until recently the identification of genetic variants contributing to these 'complex diseases' has been slow and arduous 1 . Genome-wide association studies (GWAS), in which several hundred thousand to more than a million single nucleotide polymorphisms (SNPs) are assayed in thousands of individuals, represent a powerful new tool for investigating the genetic architecture of complex diseases 1, 2. In the past few years, these studies have identified hundreds of genetic variants associated with such conditions and have provided valuable insights into the complexities of their genetic architecture3 , 4.The genome-wide association (GWA) method represents an important advance compared to 'candidate gene' studies, in which sample sizes are generally smaller and the variants assayed are limited to a selected few, often on the basis of imperfect understanding of biological pathways and often yielding associations that are difficult to replicate 5,6. GWAS are also an important step beyond family-based linkage studies, in which inheritance patterns are related to several hundreds to thousands of genomic markers. Despite many clear successes in singlegene 'Mendelian' disorders7 , 8, the limited success of linkage studies in complex diseases has been attributed to their low power and resolution for variants of modest effect 9-11 .The underlying rationale for GWAS is the 'common disease, common variant' hypothesis, positing that common diseases are attributable in part to allelic variants present in more than 1-5% of the population12 -14. They have been facilitated by the development of commercial 'SNP chips' or arrays that capture most, although not all, common variation in the genome. Although the allelic architecture of some conditions, notably age-related macular degeneration, for the most part reflects the contributions of several variants of large effect (defined loosely here as those increasing disease risk by twofold or more), most common variants individually or in combination confer relatively small increments in risk (1.1-1.5-fold) and explain only a small proportion of heritability-the portion of phenotypic variance in a population attributable to additive ...

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On autopsy, a patient is found to have hypertrophic cardiomyopathy. The patient’s family pursues genetic testing that shows a “likely pathogenic” variant for the condition on the basis of a study in an original research publication. Given the dominant inheritance of the condition and the risk of sudden cardiac death, other family members are tested for the genetic variant to determine their risk. Several family members test negative and are told that they are not at risk for hypertrophic cardiomyopathy and sudden cardiac death, and those who test positive are told that they need to be regularly monitored for cardiomyopathy on echocardiography. Five years later, during a routine clinic visit of one of the genotype-positive family members, the cardiologist queries a database for current knowledge on the genetic variant and discovers that the variant is now interpreted as “likely benign” by another laboratory that uses more recently derived population-frequency data. A newly available testing panel for additional genes that are implicated in hypertrophic cardiomyopathy is initiated on an affected family member, and a different variant is found that is determined to be pathogenic. Family members are retested, and one member who previously tested negative is now found to be positive for this new variant. An immediate clinical workup detects evidence of cardiomyopathy, and an intracardiac defibrillator is implanted to reduce the risk of sudden cardiac death.

The National Alzheimer's Coordinating Center (NACC) is responsible for developing and maintaining a database of participant information collected from the 29 Alzheimer's Disease Centers (ADCs) funded by the National Institute on Aging (NIA). The NIA appointed the ADC Clinical Task Force to determine and define an expanded, standardized clinical data set, called the Uniform Data Set (UDS). The goal of the UDS is to provide ADC researchers a standard set of assessment procedures, collected longitudinally, to better characterize ADC participants with mild Alzheimer disease and mild cognitive impairment in comparison with nondemented controls. NACC implemented the UDS (September 2005) by developing data collection forms for initial and follow-up visits based on Clinical Task Force definitions, a relational database, and a data submission system accessible by all ADCs. The NIA requires ADCs to submit UDS data to NACC for all their Clinical Core participants. Thus, the NACC web site (https://www.alz.washington.edu) was enhanced to provide efficient and secure access data submission and retrieval systems.

A Clinical Task Force, composed of clinical leaders from Alzheimer's Disease Centers (ADC), was convened by the National Institute on Aging to develop a uniform set of assessment procedures to characterize individuals with mild Alzheimer disease and mild cognitive impairment in comparison with nondemented aging. The resulting Uniform Data Set (UDS) defines a common set of clinical observations to be collected longitudinally on ADC participants in accordance with standard methods. The UDS was implemented at all ADCs on September 1, 2005. Data obtained with the UDS are submitted to the National Alzheimer's Coordinating Center and represent a unique and valuable source of data to support and stimulate collaborative research.