A pipeline for harmonising NHS Scotland laboratory data to enable national-level analyses.

Objective: Medical laboratory data together with prescribing and hospitalisation records are three of the most used electronic health records (EHRs) for data-driven health research. In Scotland, hospitalisation, prescribing and the death register data are available nationally whereas laboratory data is captured, stored and reported from local health board systems with significant heterogeneity. For researchers or other users of this regionally curated data, working on laboratory datasets across regional cohorts requires effort and time.

A National Network of Safe Havens: Scottish Perspective.

For over a decade, Scotland has implemented and operationalized a system of Safe Havens, which provides secure analytics platforms for researchers to access linked, deidentified electronic health records (EHRs) while managing the risk of unauthorized reidentification. In this paper, a perspective is provided on the state-of-the-art Scottish Safe Haven network, including its evolution, to define the key activities required to scale the Scottish Safe Haven network's capability to facilitate research and health care improvement initiatives. A set of processes related to EHR data and their delivery in Scotland have been discussed.

and Loci Identified through Large-Scale Exome Chip Analysis Regulate Kidney Development and Function.

Genome-wide association studies have identified >50 common variants associated with kidney function, but these variants do not fully explain the variation in eGFR. We performed a two-stage meta-analysis of associations between genotypes from the Illumina exome array and eGFR on the basis of serum creatinine (eGFRcrea) among participants of European ancestry from the CKDGen Consortium (: 111,666; : 48,343). In single-variant analyses, we identified single nucleotide polymorphisms at seven new loci associated with eGFRcrea (, , and ; <3.

Epidemiology and Heritability of Major Depressive Disorder, Stratified by Age of Onset, Sex, and Illness Course in Generation Scotland: Scottish Family Health Study (GS:SFHS).

The heritability of Major Depressive Disorder (MDD) has been estimated at 37% based largely on twin studies that rely on contested assumptions. More recently, the heritability of MDD has been estimated on large populations from registries such as the Swedish, Finnish, and Chinese cohorts. Family-based designs utilise a number of different relationships and provide an alternative means of estimating heritability.

Sex-Differences in the Metabolic Health of Offspring of Parents with Diabetes: A Record-Linkage Study.

Maternal diabetes in pregnancy affects offspring health. The impact of parental diabetes on offspring health is unclear. We investigated the impact of parental diabetes on the metabolic-health of adult-offspring who did not themselves have diabetes.

Cohort Profile: Generation Scotland: Scottish Family Health Study (GS:SFHS). The study, its participants and their potential for genetic research on health and illness.

GS:SFHS is a family-based genetic epidemiology study with DNA and socio-demographic and clinical data from about 24 000 volunteers across Scotland aged 18-98 years, from February 2006 to March 2011. Biological samples and anonymized data form a resource for research on the genetics of health, disease and quantitative traits of current and projected public health importance. Specific and important features of GS:SFHS include the family-based recruitment, with the intent of obtaining family groups; the breadth and depth of phenotype information, including detailed data on cognitive function, personality traits and mental health; consent and mechanisms for linkage of all data to comprehensive routine health-care records; and 'broad' consent from participants to use their data and samples for a wide range of medical research, including commercial research, and for re-contact for the potential collection of other data or samples, or for participation in related studies and the design and review of the protocol in parallel with in-depth sociological research on (potential) participants and users of the research outcomes.

Quality, quantity and harmony: the DataSHaPER approach to integrating data across bioclinical studies.

Background: Vast sample sizes are often essential in the quest to disentangle the complex interplay of the genetic, lifestyle, environmental and social factors that determine the aetiology and progression of chronic diseases. The pooling of information between studies is therefore of central importance to contemporary bioscience. However, there are many technical, ethico-legal and scientific challenges to be overcome if an effective, valid, pooled analysis is to be achieved.

Cholesterol fractions and apolipoproteins as risk factors for heart disease mortality in older men.

Background: The relevance of blood lipid levels as risk factors for ischemic heart disease (IHD) in older people is uncertain; hence, cholesterol-lowering therapy is not routinely prescribed in older populations.

Methods: We assessed IHD mortality associations with plasma levels of total cholesterol, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, apolipoprotein B, and apolipoprotein A(1) measured in older men. Ischemic heart disease was assessed in a 7-year follow-up of a cohort of 5344 men (mean age, 76.

Data integration in eHealth: a domain/disease specific roadmap.

The paper documents a series of data integration workshops held in 2006 at the UK National e-Science Centre, summarizing a range of the problem/solution scenarios in multi-site and multi-scale data integration with six HealthGrid projects using schizophrenia as a domain-specific test case. It outlines emerging strategies, recommendations and objectives for collaboration on shared ontology-building and harmonization of data for multi-site trials in this domain.