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Speak to your GP during April, UK Bowel Cancer Awareness Month


Don’t be embarrassed to go to your GP .

A consultant at West Middlesex University Hospital is urging people to go to their GP if they have symptoms linked to bowel cancer. Dr Kevin Monahan, Consultant Gastroenterologist, runs the Family History of Bowel Cancer Clinic at West Middlesex, and is speaking out to support bowel cancer awareness month during April. He says: “If for the last three weeks you’ve had blood in your poo or it’s been looser, go and see your GP. “We know that people are reluctant to visit their GP if they experience symptoms because they’re embarrassed and worried about wasting the doctor’s time. “But it could save your life. Over 90 per cent of bowel cancer patients diagnosed with the earliest stage of the disease survive five years from diagnosis compared with only 6.6 per cent of those diagnosed with advanced disease. “Bowel cancer is the third most common cancer in the UK for men and the second most common cancer for women. Every year more than 30,000 people will develop it. An estimated 13,000 people die annually from bowel cancer. “Many people worry about getting bowel cancer, sometimes because a relative has had it. At West Middlesex I run a Family History of Bowel Cancer Clinic specifically for those people who may be at higher risk of developing the disease. “The cause of most bowel cancers is not known, but we do know that some risk factors can increase your chances of developing cancer. This includes having one close relative aged under 50 or at least two close relatives on the same side of the family who developed bowel cancer at any age. “If these apply to your family and you’re worried about your risk of developing bowel cancer, you may want to talk to your GP. If your GP thinks there’s a chance you may have an increased risk of developing bowel cancer because of your family history, they can refer you to the Family History of Bowel Cancer Clinic here or elsewhere for advice and treatment.”

via Don’t be embarrassed to go to your GP.

 

Family Health History | Genetic Alliance


Family Health History

A peek into the past can reveal a lot about your future.

Family health history is the story of diseases that run in your family. It is one part of the entire history of your family. Along with culture, values, environment, and behaviors, family health history influences the way you live your life. Learning about your family health history can help you make healthy choices: it is a cheap, easy way to improve your own health and the health of your family. Share the information you gather with your healthcare provider to further reduce your risk of disease and create a partnership around your health.

Check out the Does It Run In the Family? toolkit in English and Spanish! “A Guide to Family Health History” explains the importance of family health history, how to collect it, and how to organize it. “A Guide to Genetics and Health” explains genetics 101 and gives information on conditions that can run in the family, such as heart disease, diabetes, and cancer.

Customize these booklets for your family, organization, or community.

A Guide to Family Health History, English version, cover A Guide to Family Health History English

A Guide for Understanding Genetics and Health, English version, cover A Guide for Understanding Genetics and Health English

A Guide to Family Health History, Spanish version, cover A Guide to Family Health History Spanish

A Guide for Understanding Genetics and Health, Spanish version, cover A Guide for Understanding Genetics and Health Spanish

“A Guide to Family Health History” is also available in Chinese.

View several different versions on the Genetic Alliance YouTube Channel.

Tips For Collecting Your Family Health History

Learn all you can about your family’s health!

How do I collect family health history?

Talk to your family!

Holidays and other family events (birthdays, weddings, religious gatherings) provide a great opportunity to ask family members about their lives.

Plan individual conversations to get more information.

Use what you have—existing charts or trees, photo albums, baby books, birthday date books, etc.

Send a survey. This can be part of a holiday newsletter or school project.

What information should I collect?

Collect this information for you, your parents, siblings, and children, and then move on to the extended family:

  • name and relationship to you (myself, parent, child, etc.)
  • ethnicity, race, and/or origins of family
  • place and date of birth (or your best guess—for example, “1940s”)
  • if deceased, age and cause of death
  • health history—include conditions such as heart disease, diabetes, and cancer—and when the disease started
  • lifestyle (occupation, exercise, diet, habits such as smoking and regular doctor check-ups)

Collect stories about your heritage and culture. This is an excellent opportunity to preserve your family’s memories.

“Conversations about family health history should be ongoing, not a one-time topic to be discussed and forgotten. What you learn can shape your future and even save your life.”

Sharon Terry, President & CEO, Genetic Alliance

What should I do with the information I collect?

Bring it to your healthcare provider. S/he might refer you to a genetics specialist or recommend early screening.

Use it to make healthy lifestyle choices. You can change your diet and exercise habits to reduce your risk for many conditions.

Share it with your family. Shared knowledge can lead to support.

Keep adding to your family health history. It is a lifelong process!

For more family health history resources, click here.

via Family Health History | Genetic Alliance.

 

PLOS Genetics: Comparison of Family History and SNPs for Predicting Risk of Complex Disease


Authors: Chuong B. Do, David A. Hinds, Uta Francke, Nicholas Eriksson

Abstract

The clinical utility of family history and genetic tests is generally well understood for simple Mendelian disorders and rare subforms of complex diseases that are directly attributable to highly penetrant genetic variants. However, little is presently known regarding the performance of these methods in situations where disease susceptibility depends on the cumulative contribution of multiple genetic factors of moderate or low penetrance. Using quantitative genetic theory, we develop a model for studying the predictive ability of family history and single nucleotide polymorphism (SNP)–based methods for assessing risk of polygenic disorders. We show that family history is most useful for highly common, heritable conditions (e.g., coronary artery disease), where it explains roughly 20%–30% of disease heritability, on par with the most successful SNP models based on associations discovered to date. In contrast, we find that for diseases of moderate or low frequency (e.g., Crohn disease) family history accounts for less than 4% of disease heritability, substantially lagging behind SNPs in almost all cases. These results indicate that, for a broad range of diseases, already identified SNP associations may be better predictors of risk than their family history–based counterparts, despite the large fraction of missing heritability that remains to be explained. Our model illustrates the difficulty of using either family history or SNPs for standalone disease prediction. On the other hand, we show that, unlike family history, SNP–based tests can reveal extreme likelihood ratios for a relatively large percentage of individuals, thus providing potentially valuable adjunctive evidence in a differential diagnosis.

Author Summary

In clinical practice, obtaining a detailed family history is often considered the standard-of-care for characterizing the inherited component of an individual’s disease risk. Recently, genetic risk assessments based on the cumulative effect of known single nucleotide polymorphism (SNP) disease associations have been proposed as another potentially useful source of information. To date, however, little is known regarding the predictive power of each approach. In this study, we develop models based on quantitative genetic theory to analyze and compare family history and SNP–based models. Our models explain the impact of disease frequency and heritability on performance for each method, and reveal a wide range of scenarios (16 out of the 23 diseases considered) where SNP associations may already be better predictors of risk than family history. Our results confirm the difficulty of obtaining accurate prediction when SNP or family history–based methods are used alone, and they show the benefits of combining information from the two approaches. They also suggest that, in some situations, SNP associations may be potentially useful as supporting evidence alongside other types of clinical information. To our knowledge, this study is the first broad comparison of family history– and SNP–based methods across a wide range of health conditions.

via PLOS Genetics: Comparison of Family History and SNPs for Predicting Risk of Complex Disease.

The significance of ENCODE’s human genome analysis


The results of one of the biggest efforts yet to understand the complexity and meaning of human genomic data were published last month by the ENCODE (Encyclopedia of DNA Elements) consortium.

This impressive undertaking brings new understanding to the functional aspects of the genome and can probably be considered the most significant genomic discovery step since the sequencing of the whole human genome in 2000. The ENCODE project assigned biochemical function to about 80% of the genome, and in particular to elements outside of the well-studied protein-coding regions.

The findings of the ENCODE consortium – comprising over 400 researchers working in 32 laboratories across the world – indicate that a much greater proportion of the genome is biologically active than had previously been thought, and should effectively dispel the notion of ‘junk’ DNA.

The results of functional analyses on 147 different cell types demonstrate that at least 80% of the genome performs a specific function – mostly regulating the activity of the 2% that comprises protein-encoding genes. The work identified some 4 million regulatory elements in total, many of which are located far away on the genome from the gene they control.

This is arguably the most significant step forward in our understanding of how the human genome works since the releases of the initial draft sequence in 2000 and the final draft in 2003. At that time it was deeply surprising to many to find that humans possessed only around 20,000 genes occupying less than 2% of the genome, leading some to label the other 98% as ‘junk’ DNA.

Evidence from functional and genome-wide association studies over the years has made this an increasingly defunct term as it became apparent that a large proportion of the single base mutations that cause disease fell between gene coding regions, but this new comprehensive analysis should put an end to the idea once and for all.

Dr Ewan Birney of the European Bioinformatics Institute (EBI) in Cambridge who coordinated the data analysis said “This will give researchers a whole new world to explore and ultimately, it’s hoped, will lead to new treatments”. He also pointed out that the job was still far from done, and that deep characterisation is probably only around 10% complete. It is quite possible that much of the remaining 20% of the genome has a functional role that has yet to be identified.

The thirty papers can be freely accessed by all in the journals Nature, Genome Biology and Genome Research.

The mapping provides new insights into gene organisation and most of all, mechanisms of regulation. A central goal in biology – understanding the enormous diversity of gene expression in different cell types under various physiological conditions – can be considered partly achieved.

The project yielded invaluable information on the human transcriptional regulatory network with systematic analyses of transcription factors, chromatin structure and regulatory modifications. All these findings shine new light on our concept of the gene.

Some of the newly identified elements correspond to sequence variants linked to human disease, and can therefore guide interpretation of these variations. Genome-wide association studies have previously identified many noncoding variants associated with common diseases and traits. Such variants systematically perturb transcription, alter chromatin states, and form regulatory networks. ENCODE’s results point to the involvement of regulatory DNA variation in common human disease and provide pathogenic insights into diverse disorders.

The publication of such a detailed analysis of the functionalities of the human genome has understandably generated much enthusiasm among scientists and general public alike. Confirmation that a far larger chunk of our genome is biologically active than previously thought has been an exciting discovery and researchers hope the findings will lead to a deeper understanding of numerous diseases.

It is however important to remember, and for the scientific community to clearly acknowledge, that despite these fantastic results it may be many years before patients see any benefits from the project. Better understanding of the functional complexity of the human genome will undeniably lead to improved control of disease and to better treatments, but the road to clinical implications and applications is still long and difficult.

Keywords: Bioinformatics, Biomarkers, Disease Susceptibility (Genetic), Opinion, Post-Genomic Projects
English: View of ENCODE project tracks in the ...

English: View of ENCODE project tracks in the UCSC Genome browser (Photo credit: Wikipedia)

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