Antecedents of Attachment Disorganization across the First Year: Interactions among Child and Parent Variables

Disorganized attachmentis seen as reflecting an infant’s lack of strategyfor coping with the stress of the Strange Situation procedure (SSP; Ainsworth et al., 1978) The identification of disorganized attachment by Main and Solomon (1986) generated a large body of research into its antecedents and consequences. Despite these advances, however, 1)few studies have employed a prospective longitudinal designto clarify antecedents of disorganization, and 2)most research has focused on predicting disorganization from single risk factors, rarely investigating possible interactions among child and parent or environmental variables. The current study investigated the development of disorganized attachment across the first year from a prospective longitudinal perspectivefrom 3 –13 months. A primary goal was to employ a transactional modelto predict disorganization at the end of the first year, with a focus on interactions among a variety of child (gender, stressful child characteristics) and parent variables (parenting stress, maternal behaviour, child care)

Behavioural and Affective Precursors to Disorganized Attachment in the Still-face Procedure at 4-months

We explored whether disorganization in the SSP at 13-months could be predicted from infant affect and behaviour in the SFP at 4- months. We hypothesized that infants in disorganized relationships would have the most difficulty regulating their affect and behaviour in the SFP. Infants in disorganized relationships were expected to display greater negativity (e.g., crying, negative vocalizations, stress indicators such as spitting up) throughout the SFP, compared to those in organized relationships

Both Maternal Sensitivity and Atypical Maternal Behavior Independently Predict Attachment Security and Disorganization in Adolescent Mother–infant Dyads

On the basis of these findings, at odds with current models of the origins of secure vs disorganized attachment, the current study examined the association between distinct qualities of maternal interaction and attachment in a single study. The participants in the current study were adolescent mothers and their infants, a population that has been shown to be at substantial developmental risk and to exhibit a range of markedly atypical interactions with their infants (Jaffee, Caspi, Moffitt, Belsky, and Silva, 2001)

Disorganized Attachment and Mother-Toddler Interactive Behavior in a Problem-Solving Task

PURPOSE: To examine emotional and behavioral regulation and Disorganized attachment at 24-months in a high-risk sample of adolescent mother-toddler dyads. RESULTS: Disorganization was associated with 1)increased toddler negativity and a lower quality of experience and 2)decreased levels of maternal support and assistance during the problem-solving tasks. CONCLUSION: These findings offer converging support for the suggestion that Disorganized dyads experience marked difficulties in emotional and behavioral regulation

Aptamer-based multiplexed proteomic technology for biomarker discovery

Interrogation of the human proteome in a highly multiplexed and efficient manner remains a coveted and challenging goal in biology. We present a new aptamer-based proteomic technology for biomarker discovery capable of simultaneously measuring thousands of proteins from small sample volumes (15 [mu]L of serum or plasma). Our current assay allows us to measure ~800 proteins with very low limits of detection (1 pM average), 7 logs of overall dynamic range, and 5% average coefficient of variation. This technology is enabled by a new generation of aptamers that contain chemically modified nucleotides, which greatly expand the physicochemical diversity of the large randomized nucleic acid libraries from which the aptamers are selected. Proteins in complex matrices such as plasma are measured with a process that transforms a signature of protein concentrations into a corresponding DNA aptamer concentration signature, which is then quantified with a DNA microarray. In essence, our assay takes advantage of the dual nature of aptamers as both folded binding entities with defined shapes and unique sequences recognizable by specific hybridization probes. To demonstrate the utility of our proteomics biomarker discovery technology, we applied it to a clinical study of chronic kidney disease (CKD). We identified two well known CKD biomarkers as well as an additional 58 potential CKD biomarkers. These results demonstrate the potential utility of our technology to discover unique protein signatures characteristic of various disease states. More generally, we describe a versatile and powerful tool that allows large-scale comparison of proteome profiles among discrete populations. This unbiased and highly multiplexed search engine will enable the discovery of novel biomarkers in a manner that is unencumbered by our incomplete knowledge of biology, thereby helping to advance the next generation of evidence-based medicine

Defining Natural History: Assessment of the Ability of College Students to Aid in Characterizing Clinical Progression of Niemann-Pick Disease, Type C

Niemann-Pick Disease, type C (NPC) is a fatal, neurodegenerative, lysosomal storage disorder. It is a rare disease with broad phenotypic spectrum and variable age of onset. These issues make it difficult to develop a universally accepted clinical outcome measure to assess urgently needed therapies. To this end, clinical investigators have defined emerging, disease severity scales. The average time from initial symptom to diagnosis is approximately 4 years. Further, some patients may not travel to specialized clinical centers even after diagnosis. We were therefore interested in investigating whether appropriately trained, community-based assessment of patient records could assist in defining disease progression using clinical severity scores. In this study we evolved a secure, step wise process to show that pre-existing medical records may be correctly assessed by non-clinical practitioners trained to quantify disease progression. Sixty-four undergraduate students at the University of Notre Dame were expertly trained in clinical disease assessment and recognition of major and minor symptoms of NPC. Seven clinical records, randomly selected from a total of thirty seven used to establish a leading clinical severity scale, were correctly assessed to show expected characteristics of linear disease progression. Student assessment of two new records donated by NPC families to our study also revealed linear progression of disease, but both showed accelerated disease progression, relative to the current severity scale, especially at the later stages. Together, these data suggest that college students may be trained in assessment of patient records, and thus provide insight into the natural history of a disease

Genetics of rheumatoid arthritis contributes to biology and drug discovery

A major challenge in human genetics is to devise a systematic strategy to integrate disease-associated variants with diverse genomic and biological datasets to provide insight into disease pathogenesis and guide drug discovery for complex traits such as rheumatoid arthritis (RA)1. Here, we performed a genome-wide association study (GWAS) meta-analysis in a total of >100,000 subjects of European and Asian ancestries (29,880 RA cases and 73,758 controls), by evaluating ~10 million single nucleotide polymorphisms (SNPs). We discovered 42 novel RA risk loci at a genome-wide level of significance, bringing the total to 1012–4. We devised an in-silico pipeline using established bioinformatics methods based on functional annotation5, cis-acting expression quantitative trait loci (cis-eQTL)6, and pathway analyses7–9 – as well as novel methods based on genetic overlap with human primary immunodeficiency (PID), hematological cancer somatic mutations and knock-out mouse phenotypes – to identify 98 biological candidate genes at these 101 risk loci. We demonstrate that these genes are the targets of approved therapies for RA, and further suggest that drugs approved for other indications may be repurposed for the treatment of RA. Together, this comprehensive genetic study sheds light on fundamental genes, pathways and cell types that contribute to RA pathogenesis, and provides empirical evidence that the genetics of RA can provide important information for drug discovery