This could be possible if the Cardinals decide tha

first_imgThis could be possible if the Cardinals decide that theydo not want to pay Kolb the $7 million roster bonus he isdue in March, and cut him from the team and opt to “sufferthe cap hit rather than invest further in him.”Kolb was 2-6 as a starter before he suffered multipleinjuries this season, while backup John Skelton proceededwith a record of 6-2. D-backs president Derrick Hall: Franchise ‘still focused on Arizona’ Comments   Share   Adding to the rumors about the Arizona Cardinals startingquarterback situation is the idea of the team deciding tocut its losses and release Kevin Kolb. Cleveland.com writer Tony Grossi made thesuggestion that Kolb would be a good fit with the Browns,where they run the West Coast offense the QB knows butdoesn’t run in Arizona.Kolb could also be a good fit because he “was drafted byPhiladelphia partly based on evaluations made by [GeneralManager Tom] Heckert and Coach Pat Shurmur — the Browns’top two football men,” acording to Grossi. Shurmur was theEagles’ quarterbacks coach and Heckert was the team’s GMin 2007. Top Stories center_img Cardinals expect improving Murphy to contribute right away What an MLB source said about the D-backs’ trade haul for Greinke Nevada officials reach out to D-backs on potential relocationlast_img read more

New genetic risk score could predict obesity odds

first_img iStock.com/Rostislav_Sedlacek Scientists say they can analyze genetic variations to predict who is most at risk of becoming obese. Sign up for our daily newsletter Get more great content like this delivered right to you! Country Email By Giorgia GuglielmiApr. 18, 2019 , 11:00 AM New genetic ‘risk score’ could predict obesity oddscenter_img Country * Afghanistan Aland Islands Albania Algeria Andorra Angola Anguilla Antarctica Antigua and Barbuda Argentina Armenia Aruba Australia Austria Azerbaijan Bahamas Bahrain Bangladesh Barbados Belarus Belgium Belize Benin Bermuda Bhutan Bolivia, Plurinational State of Bonaire, Sint Eustatius and Saba Bosnia and Herzegovina Botswana Bouvet Island Brazil British Indian Ocean Territory Brunei Darussalam Bulgaria Burkina Faso Burundi Cambodia Cameroon Canada Cape Verde Cayman Islands Central African Republic Chad Chile China Christmas Island Cocos (Keeling) Islands Colombia Comoros Congo Congo, the Democratic Republic of the Cook Islands Costa Rica Cote d’Ivoire Croatia Cuba Curaçao Cyprus Czech Republic Denmark Djibouti Dominica Dominican Republic Ecuador Egypt El Salvador Equatorial Guinea Eritrea Estonia Ethiopia Falkland Islands (Malvinas) Faroe Islands Fiji Finland France French Guiana French Polynesia French Southern Territories Gabon Gambia Georgia Germany Ghana Gibraltar Greece Greenland Grenada Guadeloupe Guatemala Guernsey Guinea Guinea-Bissau Guyana Haiti Heard Island and McDonald Islands Holy See (Vatican City State) Honduras Hungary Iceland India Indonesia Iran, Islamic Republic of Iraq Ireland Isle of Man Israel Italy Jamaica Japan Jersey Jordan Kazakhstan Kenya Kiribati Korea, Democratic People’s Republic of Korea, Republic of Kuwait Kyrgyzstan Lao People’s Democratic Republic Latvia Lebanon Lesotho Liberia Libyan Arab Jamahiriya Liechtenstein Lithuania Luxembourg Macao Macedonia, the former Yugoslav Republic of Madagascar Malawi Malaysia Maldives Mali Malta Martinique Mauritania Mauritius Mayotte Mexico Moldova, Republic of Monaco Mongolia Montenegro Montserrat Morocco Mozambique Myanmar Namibia Nauru Nepal Netherlands New Caledonia New Zealand Nicaragua Niger Nigeria Niue Norfolk Island Norway Oman Pakistan Palestine Panama Papua New Guinea Paraguay Peru Philippines Pitcairn Poland Portugal Qatar Reunion Romania Russian Federation Rwanda Saint Barthélemy Saint Helena, Ascension and Tristan da Cunha Saint Kitts and Nevis Saint Lucia Saint Martin (French part) Saint Pierre and Miquelon Saint Vincent and the Grenadines Samoa San Marino Sao Tome and Principe Saudi Arabia Senegal Serbia Seychelles Sierra Leone Singapore Sint Maarten (Dutch part) Slovakia Slovenia Solomon Islands Somalia South Africa South Georgia and the South Sandwich Islands South Sudan Spain Sri Lanka Sudan Suriname Svalbard and Jan Mayen Swaziland Sweden Switzerland Syrian Arab Republic Taiwan Tajikistan Tanzania, United Republic of Thailand Timor-Leste Togo Tokelau Tonga Trinidad and Tobago Tunisia Turkey Turkmenistan Turks and Caicos Islands Tuvalu Uganda Ukraine United Arab Emirates United Kingdom United States Uruguay Uzbekistan Vanuatu Venezuela, Bolivarian Republic of Vietnam Virgin Islands, British Wallis and Futuna Western Sahara Yemen Zambia Zimbabwe Click to view the privacy policy. Required fields are indicated by an asterisk (*) Next, the researchers tested how accurately the score predicted BMI and obesity in some 300,000 additional individuals—from newborns to middle-aged people. Among the adults with the highest risk scores, 83% were overweight or obese, the researchers report today in Cell. But 17% of people with those scores had a BMI within the normal range, and 0.2% were underweight, they also note.The adults with the highest risk scores weighed on average 13 kilograms more than those with the lowest scores, and they were 25 times as likely to be severely obese, or more than 45 kilograms overweight. “What’s striking is not just the weight,” says Sekar Kathiresan, a cardiologist and geneticist at Massachusetts General Hospital in Boston and the Broad Institute in Cambridge, Massachusetts, who led the study. “If you have a high risk score for obesity, you’re at high risk for heart attack, stroke, diabetes, hypertension, heart failure, and blood clots in the legs.”Another surprising result is how early in life the impact of these scores becomes evident, says Nilanjan Chatterjee, a geneticist at Johns Hopkins University in Baltimore, Maryland. High- and low-risk individuals start to show significant differences in body weight at about 3 years of age; by the time kids turned 18, those with the highest risk weighed on average 12 kilograms more than those with the lowest—a gap similar to that seen among middle-aged people.Spotting children with a high risk of obesity early could help parents and physicians intervene, Kathiresan says. But what kind of intervention should be put in place is still unclear. Others worry that people with a high genetic risk for obesity won’t be motivated to change their lifestyle, especially if they think that the chance of gaining extra weight is written in their DNA. “If you give an 8-year-old a genetic risk score, what do you expect them to do?” asks Cecile Janssens, an epidemiologist at Emory University in Atlanta. “They still have to go through puberty and all the college partying.”Ruth Loos, a genetic epidemiologist at the Icahn School of Medicine at Mount Sinai in New York City, echoes this concern. People giving up and blaming their genetics, she says, is “the last thing we want as obesity researchers.”Researchers also caution that because genetic risk scores so far have largely been generated and validated in data sets made up mainly of people of European descent, the extent to which they can be applied to people of other ethnicities might be limited. These risk scores for obesity are optimal for white people, and their predictive power will drop for other ethnic groups, Kathiresan says.Loos adds that, because obesity is influenced by both genetic and environmental factors such as diet and exercise, genetic risk scores should be used in combination with other predictors such as family history. Knowing whether one or both parents are obese or were obese during childhood is important, because that could reflect the environment they’ve created for their children—the way they eat, and whether they’re physically active, she says. “Any score that captures genetic predisposition will never accurately predict future obesity. … You need to account for that environmental part.” Millions of subtle variations in the human DNA sequence, or genome, hold the key to a host of conditions, from breast cancer to heart disease. Now, researchers say they can analyze such variations to predict who is most at risk of becoming obese.The new genetic risk score provides the best DNA-based forecast yet for obesity, say other scientists who have reviewed the work. But they also warn that the score has serious limitations, as it only suggests a likely weight range—and a wide one—for each person. And because excess weight gain often kicks in early in life, physicians and parents would need to get the score for children early for it to make a difference.To develop the new score, researchers used data from a previous genomewide study, which scoured the genomes of more than 300,000 people for 2.1 million genetic variants affecting body mass index (BMI), a ratio of a person’s height and weight often used as a proxy for obesity. Then, they compared that with the known weights and BMIs of those people, calculated the impact of each variant on BMI, and integrated that information into a single number, called a “polygenic risk score.”last_img read more