All individuals with variants in gene HBM

Legend

Please note that a short description of a certain column can be displayed when you move your mouse cursor over the column's header and hold it still. Below, a more detailed description is shown per column.

ID_report: ID of the individual that can be publically shared, e.g. as listed in a publication

Reference: reference to publication describing the individual/family, possibly giving more phenotypic details than listed in this database entry, incl. link to PubMed or other source, e.g. "den Dunnen ASHG2003 P2346"

Remarks: remarks about the individual

Gender: gender individual
All options:

? = unknown
- = not applicable
F = female
M = male
rF = raised as female
rM = raised as male

Consanguinity: indicates whether the parents are related (consanguineous), not related (non-consanguineous) or whether consanguinity is not known (unknown)
All options:

no = non-consanguineous parents
yes = consanguineous parents
likely = consanguinity likely
? = unknown
- = not applicable

Country: where (country) does the individual live/recently came from. Give additional details (population, specific sub-group) and when parents come from different countries in "Population". Belgium = individual lives in/recently came from Belgium, (France) = reported by laboratory in France, individual's country of origin not sure
All options:

? (unknown)
- (not applicable)
Afghanistan
(Afghanistan)
Albania
(Albania)
Algeria
(Algeria)
American Samoa
(American Samoa)
Andorra
(Andorra)
Angola
(Angola)
Anguilla
(Anguilla)
Antarctica
(Antarctica)
Antigua and Barbuda
(Antigua and Barbuda)
Argentina
(Argentina)
Armenia
(Armenia)
Aruba
(Aruba)
Australia
(Australia)
Austria
(Austria)
Azerbaijan
(Azerbaijan)
Bahamas
(Bahamas)
Bahrain
(Bahrain)
Bangladesh
(Bangladesh)
Barbados
(Barbados)
Belarus
(Belarus)
Belgium
(Belgium)
Belize
(Belize)
Benin
(Benin)
Bermuda
(Bermuda)
Bhutan
(Bhutan)
Bolivia
(Bolivia)
Bosnia and Herzegovina
(Bosnia and Herzegovina)
Botswana
(Botswana)
Bouvet Island
(Bouvet Island)
Brazil
(Brazil)
British Indian Ocean Territory
(British Indian Ocean Territory)
Brunei Darussalam
(Brunei Darussalam)
Bulgaria
(Bulgaria)
Burkina Faso
(Burkina Faso)
Burundi
(Burundi)
Cambodia
(Cambodia)
Cameroon
(Cameroon)
Canada
(Canada)
Cape Verde
(Cape Verde)
Cayman Islands
(Cayman Islands)
Central African Republic
(Central African Republic)
Central Europe
Chad
(Chad)
Chile
(Chile)
China
(China)
Christmas Island
(Christmas Island)
Cocos (Keeling Islands)
(Cocos (Keeling Islands))
Colombia
(Colombia)
Comoros
(Comoros)
Congo
(Congo)
Cook Islands
(Cook Islands)
Costa Rica
(Costa Rica)
Cote D'Ivoire (Ivory Coast)
(Cote D'Ivoire (Ivory Coast))
Croatia (Hrvatska)
(Croatia (Hrvatska))
Cuba
(Cuba)
Cyprus
(Cyprus)
Czech Republic
(Czech Republic)
Denmark
(Denmark)
Djibouti
(Djibouti)
Dominica
(Dominica)
Dominican Republic
(Dominican Republic)
East Timor
(East Timor)
Ecuador
(Ecuador)
Egypt
(Egypt)
El Salvador
(El Salvador)
England
(England)
Equatorial Guinea
(Equatorial Guinea)
Eritrea
(Eritrea)
Estonia
(Estonia)
Ethiopia
(Ethiopia)
Falkland Islands (Malvinas)
(Falkland Islands (Malvinas))
Faroe Islands
(Faroe Islands)
Fiji
(Fiji)
Finland
(Finland)
France
(France)
Gabon
(Gabon)
Gambia
(Gambia)
Georgia
(Georgia)
Germany
(Germany)
Ghana
(Ghana)
Gibraltar
(Gibraltar)
Greece
(Greece)
Greenland
(Greenland)
Grenada
(Grenada)
Guadeloupe
(Guadeloupe)
Guam
(Guam)
Guatemala
(Guatemala)
Guiana, French
(Guiana, French)
Guinea
(Guinea)
Guinea-Bissau
(Guinea-Bissau)
Guyana
(Guyana)
Haiti
(Haiti)
Heard and McDonald Islands
(Heard and McDonald Islands)
Honduras
(Honduras)
Hong Kong
(Hong Kong)
Hungary
(Hungary)
Iceland
(Iceland)
India
(India)
Indonesia
(Indonesia)
Iran
(Iran)
Iraq
(Iraq)
Ireland
(Ireland)
Israel
(Israel)
Italy
(Italy)
Jamaica
(Jamaica)
Japan
(Japan)
Jordan
(Jordan)
Kazakhstan
(Kazakhstan)
Kenya
(Kenya)
Kiribati
(Kiribati)
Korea
(Korea)
Korea, North (People's Republic)
(Korea, North (People's Republic))
Korea, South (Republic)
(Korea, South (Republic))
Kosovo
(Kosovo)
Kuwait
(Kuwait)
Kyrgyzstan (Kyrgyz Republic)
(Kyrgyzstan (Kyrgyz Republic))
Laos
(Laos)
Latvia
(Latvia)
Lebanon
(Lebanon)
Lesotho
(Lesotho)
Liberia
(Liberia)
Libya
(Libya)
Liechtenstein
(Liechtenstein)
Lithuania
(Lithuania)
Luxembourg
(Luxembourg)
Macau
(Macau)
Macedonia
(Macedonia)
Madagascar
(Madagascar)
Malawi
(Malawi)
Malaysia
(Malaysia)
Maldives
(Maldives)
Mali
(Mali)
Mallorca
(Mallorca)
Malta
(Malta)
Marshall Islands
(Marshall Islands)
Martinique
(Martinique)
Mauritania
(Mauritania)
Mauritius
(Mauritius)
Mayotte
(Mayotte)
Mexico
(Mexico)
Micronesia
(Micronesia)
Moldova
(Moldova)
Monaco
(Monaco)
Mongolia
(Mongolia)
Montserrat
(Montserrat)
Morocco
(Morocco)
Mozambique
(Mozambique)
Myanmar
(Myanmar)
Namibia
(Namibia)
Nauru
(Nauru)
Nepal
(Nepal)
Netherlands
(Netherlands)
Netherlands Antilles
(Netherlands Antilles)
Neutral Zone (Saudia Arabia/Iraq)
(Neutral Zone (Saudia Arabia/Iraq))
New Caledonia
(New Caledonia)
New Zealand
(New Zealand)
Nicaragua
(Nicaragua)
Niger
(Niger)
Nigeria
(Nigeria)
Niue
(Niue)
Norfolk Island
(Norfolk Island)
Northern Ireland
(Northern Ireland)
Northern Mariana Islands
(Northern Mariana Islands)
Norway
(Norway)
Oman
(Oman)
Pakistan
(Pakistan)
Palau
(Palau)
Palestine
(Palestine)
Panama
(Panama)
Papua New Guinea
(Papua New Guinea)
Paraguay
(Paraguay)
Peru
(Peru)
Philippines
(Philippines)
Pitcairn
(Pitcairn)
Poland
(Poland)
Polynesia, French
(Polynesia, French)
Portugal
(Portugal)
Puerto Rico
(Puerto Rico)
Qatar
(Qatar)
Reunion
(Reunion)
Romania
(Romania)
Russia
(Russia)
Russian Federation
(Russian Federation)
Rwanda
(Rwanda)
S. Georgia and S. Sandwich Isls.
(S. Georgia and S. Sandwich Isls.)
Saint Kitts and Nevis
(Saint Kitts and Nevis)
Saint Lucia
(Saint Lucia)
Saint Vincent and The Grenadines
(Saint Vincent and The Grenadines)
Samoa
(Samoa)
San Marino
(San Marino)
Sao Tome and Principe
(Sao Tome and Principe)
Saudi Arabia
(Saudi Arabia)
Scotland
(Scotland)
Senegal
(Senegal)
Serbia
(Serbia)
Seychelles
(Seychelles)
Sierra Leone
(Sierra Leone)
Singapore
(Singapore)
Slovakia (Slovak Republic)
(Slovakia (Slovak Republic))
Slovenia
(Slovenia)
Solomon Islands
(Solomon Islands)
Somalia
(Somalia)
South Africa
(South Africa)
Southern Territories, French
(Southern Territories, French)
Soviet Union (former)
(Soviet Union (former))
Spain
(Spain)
Sri Lanka
(Sri Lanka)
St. Helena, Ascension and Tristan da
Cunha
(St. Helena, Ascension and Tristan da
Cunha)
St. Pierre and Miquelon
(St. Pierre and Miquelon)
Sudan
(Sudan)
Sudan, South
(Sudan, South)
Suriname
(Suriname)
Svalbard and Jan Mayen Islands
(Svalbard and Jan Mayen Islands)
Swaziland
(Swaziland)
Sweden
(Sweden)
Switzerland
(Switzerland)
Syria
(Syria)
Taiwan
(Taiwan)
Tajikistan
(Tajikistan)
Tanzania
(Tanzania)
Thailand
(Thailand)
Togo
(Togo)
Tokelau
(Tokelau)
Tonga
(Tonga)
Trinidad and Tobago
(Trinidad and Tobago)
Tunisia
(Tunisia)
Turkey
(Turkey)
Turkmenistan
(Turkmenistan)
Turks and Caicos Islands
(Turks and Caicos Islands)
Tuvalu
(Tuvalu)
Uganda
(Uganda)
Ukraine
(Ukraine)
United Arab Emirates
(United Arab Emirates)
United Kingdom (Great Britain)
(United Kingdom (Great Britain))
United States
(United States)
Uruguay
(Uruguay)
US Minor Outlying Islands
(US Minor Outlying Islands)
Uzbekistan
(Uzbekistan)
Vanuatu
(Vanuatu)
Vatican City State (Holy See)
(Vatican City State (Holy See))
Venezuela
(Venezuela)
Viet Nam
(Viet Nam)
Virgin Islands (British)
(Virgin Islands (British))
Virgin Islands (US)
(Virgin Islands (US))
Wales
(Wales)
Wallis and Futuna Islands
(Wallis and Futuna Islands)
Western Sahara
(Western Sahara)
Yemen
(Yemen)
Yugoslavia
(Yugoslavia)
Zaire
(Zaire)
Zambia
(Zambia)
Zimbabwe
(Zimbabwe)

Population: population the individual (or ancestors) belongs to; e.g. white, gypsy, Jewish-Ashkenazi, Africa-N, Sardinia, etc.

Age at death: age at which the individual deceased (when applicable):

35y = 35 years
>43y = still alive at 43y
04y08m = 4 years and 8 months
00y00m01d12h = 1 day and 12 hours
18y? = around 18 years
30y-40y = between 30 and 40 years
>54y = older than 54
? = unknown

VIP: individual/phenotype VIP-status was requested for matchmaking - need collaboration(s) to crack the case - please contact the submitter/curator. NOTE: to get VIP status ask the curator.

Data_av: are additional data available upon request: e.g. pedigree (yes/no/?)

Treatment: treatment of patient

Variants in genes: The individual has variants for this gene.

Panel size: Number of individuals this entry represents; e.g. 1 for an individual, 5 for a family with 5 affected members.

How to query this table

All list views have search fields which can be used to search data. You can search for a complete word or you can search for a part of a search term. If you enclose two or more words in double quotes, LOVD will search for the combination of those words only exactly in the order you specify. Note that search terms are case-insensitive and that wildcards such as * are treated as normal text! For all options, like "and", "or", and "not" searches, or searching for prefixes or suffixes, see the table below.

Operator	Column type	Example	Matches
	Text	Arg	all entries containing 'Arg'
space	Text	Arg Ser	all entries containing 'Arg' and 'Ser'
\|	Text	Arg\|Ser	all entries containing 'Arg' or 'Ser'
!	Text	!fs	all entries not containing 'fs'
^	Text	^p.(Arg	all entries beginning with 'p.(Arg'
$	Text	Ser)$	all entries ending with 'Ser)'
=""	Text	=""	all entries with this field empty
=""	Text	="p.0"	all entries exactly matching 'p.0'
!=""	Text	!=""	all entries with this field not empty
!=""	Text	!="p.0"	all entries not exactly matching 'p.0?'
combination	Text	*\|Ter !fs	all entries containing '*' or 'Ter' but not containing 'fs'
	Date	2020	all entries matching the year 2020
\|	Date	2020-03\|2020-04	all entries matching March or April, 2020
!	Date	!2020-03	all entries not matching March, 2020
<	Date	<2020	all entries before the year 2020
<=	Date	<=2020-06	all entries in or before June, 2020
>	Date	>2020-06	all entries after June, 2020
>=	Date	>=2020-06-15	all entries on or after June 15th, 2020
combination	Date	2019\|2020 <2020-03	all entries in 2019 or 2020, and before March, 2020
	Numeric	23	all entries exactly matching 23
\|	Numeric	23\|24	all entries exactly matching 23 or 24
!	Numeric	!23	all entries not exactly matching 23
<	Numeric	<23	all entries lower than 23
<=	Numeric	<=23	all entries lower than, or equal to, 23
>	Numeric	>23	all entries higher than 23
>=	Numeric	>=23	all entries higher than, or equal to, 23
combination	Numeric	>=20 <30 !23	all entries with values from 20 to 29, but not equal to 23

Some more advanced examples:

Example	Matches
Asian	all entries containing 'Asian', 'asian', including 'Caucasian', 'caucasian', etc.
Asian !Caucasian	all entries containing 'Asian' but not containing 'Caucasian'
Asian\|African !Caucasian	all entries containing 'Asian' or 'African', but not containing 'Caucasian'
"South Asian"	all entries containing 'South Asian', but not containing 'South East Asian'

To sort on a certain column, click on the column header or on the arrows. If that column is already selected to sort on, the sort order will be swapped. The column currently sorted on has a darker blue background color than the other columns. The up and down arrows next to the column name indicate the current sorting direction. When sorting on any field other than the default, LOVD will sort secondarily on the default sort column.

16 entries on 1 page. Showing entries 1 - 16.

Legend

How to query

Individual ID	ID_report	Reference	Remarks	Gender	Consanguinity	Country	Population	Age at death	VIP	Data_av	Treatment	Disease	Phenotype details	Variants	Panel size	Owner
00000070	-	PubMed: Bell 2011	-	-	-	-	-	-	-	-	-	-	-	1	1	Global Variome, with Curator vacancy
00000080	-	PubMed: Bell 2011	-	-	-	-	-	-	-	-	-	-	-	1	1	Global Variome, with Curator vacancy
00000093	-	PubMed: Bell 2011	-	-	-	-	-	-	-	-	-	-	-	1	1	Global Variome, with Curator vacancy
00104732	28125089-?	PubMed: He 2017, Journal: He 2017	double-blind, premarital hemoglobinopathy screening 951 individuals	-	-	China	Dai (Dehong, Xishuangbanna)	-	-	-	-	?	MCV (fL) 61.0±9.1; MCH (pg) 19.4±2.6; HbA2 (%) 13.0±7.0; HbF (%) -	1	4	Baosheng Zhu
00104733	28125089-?	PubMed: He 2017, Journal: He 2017	double-blind, premarital hemoglobinopathy screening 951 individuals	-	-	China	Dai (Dehong, Xishuangbanna)	-	-	-	-	?	MCV (fL) 70; MCH (pg) 22.3; HbA2 (%) 5.59; HbF (%) -	1	1	Baosheng Zhu
00104734	28125089-?	PubMed: He 2017, Journal: He 2017	double-blind, premarital hemoglobinopathy screening 951 individuals	-	-	China	Dai (Dehong, Xishuangbanna)	-	-	-	-	?	MCV (fL) 74.4; MCH (pg) 21.4; HbA2 (%) 2.25; HbF (%)	1	1	Baosheng Zhu
00104735	28125089-?	PubMed: He 2017, Journal: He 2017	double-blind, premarital hemoglobinopathy screening 951 individuals	-	-	China	Dai (Dehong, Xishuangbanna)	-	-	-	-	?	MCV (fL) 83.9; MCH (pg) 25.1; HbA2 (%) 7.61; HbF (%) 1.6	1	1	Baosheng Zhu
00104745	28125089-?	PubMed: He 2017, Journal: He 2017	double-blind, premarital hemoglobinopathy screening 951 individuals	-	-	China	Dai (Dehong, Xishuangbanna)	-	-	-	-	?	MCV (fL) 46.0±4.2; MCH (pg) 15.3±1.1; HbA2 (%) 13.5±0.2; HbF (%) -	1	2	Baosheng Zhu
00104749	28125089-?	PubMed: He 2017, Journal: He 2017	double-blind, premarital hemoglobinopathy screening 951 individuals	-	-	China	Dai (Dehong, Xishuangbanna)	-	-	-	-	?	MCV (fL) 46.4; MCH (pg) 14.6; HbA2 (%) -; HbF (%) -	1	1	Baosheng Zhu
00104750	28125089-?	PubMed: He 2017, Journal: He 2017	double-blind, premarital hemoglobinopathy screening 951 individuals	-	-	China	Dai (Dehong, Xishuangbanna)	-	-	-	-	?	MCV (fL) 80; MCH (pg) 28.1; HbA2 (%) 14.53; HbF (%) -	1	1	Baosheng Zhu
00104759	28125089-?	PubMed: He 2017, Journal: He 2017	double-blind, premarital hemoglobinopathy screening 951 individuals	-	-	China	Dai (Dehong, Xishuangbanna)	-	-	-	-	?	MCV (fL) 56.3±8.9; MCH (pg) 17.0±2.0; HbA2 (%) 1.9±0.8; HbF (%) -	1	8	Baosheng Zhu
00104762	28125089-?	PubMed: He 2017, Journal: He 2017	double-blind, premarital hemoglobinopathy screening 951 individuals	-	-	China	Dai (Dehong, Xishuangbanna)	-	-	-	-	?	MCV (fL) 67.0±4.5; MCH (pg) 20.8±1.4; HbA2 (%) 2.6±0.4; HbF (%) 2.4±0.6	1	75	Baosheng Zhu
00104763	28125089-?	PubMed: He 2017, Journal: He 2017	double-blind, premarital hemoglobinopathy screening 951 individuals	-	-	China	Dai (Dehong, Xishuangbanna)	-	-	-	-	?	MCV (fL) 64.9±1.7; MCH (pg) 19.9±0.9; HbA2 (%) 2.7±0.5; HbF (%) -	1	3	Baosheng Zhu
00104764	28125089-?	PubMed: He 2017, Journal: He 2017	double-blind, premarital hemoglobinopathy screening 951 individuals	-	-	China	Dai (Dehong, Xishuangbanna)	-	-	-	-	?	MCV (fL) 71; MCH (pg) 18.3; HbA2 (%) 1.71; HbF (%) -	1	1	Baosheng Zhu
00104765	28125089-?	PubMed: He 2017, Journal: He 2017	double-blind, premarital hemoglobinopathy screening 951 individuals	-	-	China	Dai (Dehong, Xishuangbanna)	-	-	-	-	?	MCV (fL) 68; MCH (pg) 20.9; HbA2 (%) 3.01; HbF (%) -	1	1	Baosheng Zhu
00448672	patient	PubMed: Soler 2024	2-generation family, 1 affected, unaffected heterozygous parents	F	-	Brazil	white	-	-	-	-	thalalpa	see paper; ..., Hb Bart's during neonatal screening; microcytic/hypochromic anemia, mild reticulocytosis	1	1	Johan den Dunnen

Legend

How to query

Global Variome shared LOVD

HBM (hemoglobin, mu)